The Diffusion of Innovative Biodiversity Conservation Policies and Practices

Received: 16 January 2017 Accepted: 10 January 2018

DOI: 10.1111/conl.12442

POLICY PERSPECTIVE

When conservation goes viral: The diﬀusion of innovative biodiversity conservation policies and practices

Michael B. Mascia1∗ Morena Mills2,3,4∗

1 Moore Center for Science, Conservation Abstract International, Arlington, Virginia, USA Despite billions of dollars invested, “getting to scale” remains a fundamental chal- 2Department of Life Sciences, Imperial Col- lege London, Ascot, Berkshire, United King- lenge for conservation donors and practitioners. Occasionally, however, a conserva- dom tion intervention will “go viral,” with rapid, widespread adoption that transforms the 3 Centre for Biodiversity and Conservation relationship between people and nature across large areas. The factors that shape rates Science, University of Queensland, St. Lucia, Australia and patterns of conservation interventions remain unclear, puzzling scientists and hin- 4Australian Research Council (ARC) Centre dering evidence-based policymaking. Diffusion of innovation theory—the study of of Excellence in Environmental Decisions, the how and why innovations are adopted, and the rates and patterns of adoption— University of Queensland, St. Lucia, Australia provides a novel lens for examining rates and patterns in the establishment of conser- Correspondence Michael B. Mascia, Moore Center for Science, vation interventions. Case studies from Tanzania and the Pacific illustrate that charac- Conservation International, 2011 Crystal teristics of the innovation, of the adopters, and of the social-ecological context shape Drive, Arlington, VA 22202, USA. spatial and temporal dynamics in the diffusion of community-centered conservation Email: [email protected] interventions. Differential trends in adoption mirrored the relative advantage of inter- ∗Both authors contributed equally to this work. ventions to local villagers and villager access to external technical assistance. Theo- Correction added on 9 May 2018, after first online publication on 29 January 2018: The ries of innovation diffusion highlight new arenas for conservation research and pro- caption of Figure 1 was updated to correct color vide critical insights for conservation policy and practice, suggesting the potential to descriptions of lines within the figure that were previously transposed. empower donors and practitioners with the ability to catalyze conservation at scale— and to do so at less cost and with longer-lasting impacts.

KEYWORDS biodiversity conservation, CBNRM, communal conservancies, diﬀusion, environmental governance, innovation, marine protected areas, wildlife conservancies

1 INTRODUCTION community-based natural resource management systems, certification schemes, and other policies, programs, and projects Biodiversity conservation efforts are widespread and prolif- designed to conserve biodiversity (hereafter, conservation erating rapidly, but Parties to the Convention on Biologi- interventions; Gullison, 2003; Kellert, Mehta, Ebbin, & Licht- cal Diversity are unlikely to meet global conservation tar- enfeld, 2000; Mascia et al., 2014). A history of “fads” gets by 2020 (Butchart et al., 2015). For example, although and “hot moments,” however, demonstrates the potential some countries have exceeded targets for spatial extent of for rapid, widespread adoption of novel conservation strate- protected areas, others lag behind (Fox et al., 2012). Even gies and tactics (Radeloff et al., 2013; Redford, Padoch, countries that have met these area-based targets often over- & Sunderland, 2013), a necessary—but insufficient—step represent some ecosystems and leave others largely unpro- to address biodiversity loss and other global environmental tected (Devillers et al., 2015). Similar challenges plague challenges.

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Conservation Letters. 2018;11:e12442. wileyonlinelibrary.com/journal/conl 1of9 https://doi.org/10.1111/conl.12442 2of9 MASCIA AND MILLS

The factors that shape patterns and trends in establishment (1) innovation characteristics; (2) adopter characteristics; and of conservation interventions remain unclear, puzzling scien- (3) the social-ecological context surrounding an innovation tists and hindering evidence-based policymaking (Fox et al., and its adopters (Rogers, 2003). Within each set, numerous 2012). Researchers have examined these spatial and tempo- variables influence adoption; here, these variables may shape ral dynamics, but evidence is limited and largely atheoretical rates and patterns of adoption of conservation interventions. (Fox et al., 2012). Protected areas, for example, are prefer- Though most diffusion of innovation research focuses on entially located in areas of endemic and threatened species adoption among individuals, the theory also addresses adop- (Fox et al., 2012; Loucks, Ricketts, Naidoo, Lamoreux, & tion among social groups, organizations, and governments. Hoekstra, 2008) and low opportunity costs (Devillers et al., 2015; Joppa & Pfaff, 2009). These spatial biases vary among 2.1 Innovation characteristics ecoregions (Loucks et al., 2008), likely because subnational and local processes shape protected area siting decisions The characteristics of an innovation, as perceived by potential (Fox et al., 2012), including government policies (Alcala & adopters, shape the likelihood of adoption. The relative Russ, 2006), stakeholder participation (Dalton, 2006), and advantage of an innovation (i.e., perceived superiority rela- donor funding (Miller, Agrawal, & Roberts, 2013). Conser- tive to status quo and other options), for example, accelerates vation actions appear particularly rapid amid transformative adoption (Pannell et al., 2006; Rogers, 2003). The observ- sociopolitical change (Radeloff et al., 2013). ability of an innovation, and its compatibility with adopter Diffusion of innovation theory (Rogers, 2003)—the study beliefs and values, fosters more rapid and widespread adop- of how and why innovations are adopted by people, groups, tion (Rogers, 2003). Flexible innovations, which adopters organizations, or countries (hereafter adopters), and rates tailor to their needs, and those that are simple (i.e., low and patterns of adoption—provides a novel lens for exam- complexity) and can be trialed (i.e., trialability), are more ining establishment of conservation interventions. Innova- rapidly adopted (Greenhalgh, Robert, MacFarlane, Bate, & tions are ideas, practices, or objects perceived as new by Kyriakidou, 2004; Pannell et al., 2006). These characteristics adopters (Rogers, 2003); diffusion is the process by which are not fixed attributes of the innovation itself, but, rather, “prior adoption of a trait or practice in a population alters the reflect the interplay between the innovation, adopters, mode probability of adoption for remaining non adopters” (Strang, of implementation, and broader social-ecological context 1991). In the social sciences, diffusion of innovation the- (Greenhalgh et al., 2004). ory has been applied widely to medicine, business, agriculture, and other sectors (Wejnert, 2002). Surprisingly, diffusion of innovation theory has never been applied to examine 2.2 Adopter characteristics rates and patterns in biodiversity conservation interventions, Characteristics of potential adopters of an innovation also though studies have examined adoption processes (Abernethy, shape rates and patterns of diffusion. Individual personality Bodin, Olsson, Hilly, & Schwarz, 2014; Korhonen, Hujala, & traits such as psychological strength, self-confidence, and Kurttila, 2013) and other environmental initiatives (Pannell risk orientation increase adoption (Rogers, 2003), as do et al., 2006; Vasi 2006). socioeconomic factors such as higher levels of individual To advance conservation science and inform conservation education, literacy, and economic well-being. Existing policy, we explore the potential for diffusion of innovation the- knowledge is positively correlated with adoption; individuals ory to explain the spatial and temporal dynamics of conserva- who must develop new skills and knowledge to benefit from tion interventions. First, we introduce foundational concepts an innovation are less likely to adopt (Pannell et al., 2006). in diffusion of innovation theory. We then draw upon the- With increasing time horizons, likelihood of an individual ory and existing data to examine spatial and temporal dynam- adopting an innovation with long-term relative advantage ics of conservation interventions in Tanzania and the Pacific. also increases (Pannell et al., 2006). Similarly, individuals are Finally, we consider the implications of diffusion of innova- more likely to adopt innovations as their connectedness to the tion theory for conservation science and policy. Our findings outside world increases through social engagement, contact suggest the potential to catalyze conservation at scale through with change agents, and exposure to mass media (Rogers, social science-based planning, design, and implementation. 2003). Familiarity with an innovation—through experience, peer advice, media, connections to other adopters, and advisory support—also increases adoption rates (Dolowitz & 2 DIFFUSION OF INNOVATION Marsh, 1996; Pannell et al., 2006). THEORY The position of an individual relative to others also shapes likelihood of adoption. If the relative social status of pre- Diffusion of innovation theory highlights three sets of vari- vious adopters is higher than that of prospective adopters, ables that shape rates and patterns in adoption of innovations: for example, likelihood of adoption increases within this MASCIA AND MILLS 3of9 latter group (Rogers, 2003). Conversely, structural equiva- mountains) can hinder interpersonal communication, interac- lence between past and prospective adopters may foster adoption, and social networks that foster adoption (Wejnert, 2002), tion, as individuals look to the practices adopted by others though communication technologies (e.g., mobile phones) who have similar resources, social problems, and adminis- mediate these dynamics. Similarly, compatibility and relative trative styles (Walker, 1969). The nature and position of an advantage of an innovation may vary among cultures, based individual's social networks also influence adoption rates; on societal beliefs, values, and other factors. Cultural tradi- greater interpersonal or organizational communication net- tionalism and homogeneity, for example, may limit willing- works increase likelihood of adoption (Walker, 1969). Last, ness to trial innovations (Rogers, 2003). Culture also influ- where individuals compete with each other, this competitive ences characteristics that confer social status and shapes the environment accelerates adoption relative to noncompetitive composition and structure of social networks, which, in turn, environments (Rogers, 2003; Walker, 1969). influence adoption rates and patterns (Wejnert, 2002). Many factors that shape individual behavior also influence Last, global uniformity influences adoption through three adoption of innovations by social groups, organizations, and interdependent variables (Wejnert, 2002): institutionalization, governments, though differences among actors have not been global technology, and world connectedness. Institutionaliza- fully explored (Greenhalgh et al., 2004). For example, among tion influences the spread of “approved” practices, programs, social groups and organizations, socioeconomic factors such and incentives, such as those promoted by international as degree of technological advancement, relative wealth, orga- donors or supported by state or federal governments. Global nization size, level of development, and financial resources technology, the adoption of technological innovations facil- drive adoption (Rogers, 2003); among nation-states, levels of itated through multinational organizations, spreads through development, urbanization, industrialization, wealth, educa- conservation organizations as these are either imposed or tion, and population size are positively correlated with adop- adopted locally. World connectedness influences diffusion of tion (Walker, 1969). Similarly, competition among political innovations via existing communication and media systems parties may accelerate adoption of innovation, as parties try to (e.g., television, Internet). Additionally, elements of global outdo each other by embracing novel policies and programs. uniformity influence the relative advantage and perceived Other factors that shape diffusion are unique to more com- complexity of an innovation, prospective adopters’ access to plex forms of social organization. For example, as organi- information, and connections among social and support net- zational capacity increases within organizations, these staff, works (Wejnert, 2002). facilities, and supporting services foster accelerated adoption of innovations (Walker, 1969). Decision-making structures also shape rates and patterns of adoption; decentralized decision-making structures foster adoption of innovation by 3 DIFFUSION OF INNOVATIONS IN allowing organizations to assimilate innovations more readily. CONSERVATION

2.3 Social-ecological context 3.1 Community-based conservation in Tanzania: different interventions, similar Last, rates and patterns of adoption are shaped by the social- context ecological context surrounding an innovation and its adopters. Political conditions, for example, shape adopters’ perceptions The diffusion of three conservation interventions in Tan- of and interactions with an innovation. Government policies zania demonstrates the influence of innovation characteris- can influence basic characteristics of an innovation, including tics, adopter characteristics, and context (Table 1). In 1998, its relative advantage, complexity, flexibility, and compatibil- through several pieces of legislation, Tanzania established the ity with local beliefs and values. The manner in which govern- policy foundations for three systems of participatory conser- ments interact with prospective adopters influences adoption vation (i.e., interventions): community-based forest manage- (Pannell et al., 2006); technical assistance and support, for ment (CBFM), joint forest management (JFM), and wildlife example, facilitate adoption and diffusion (Greenhalgh et al., management areas (WMAs; Blomley & Ramadhani, 2006; 2004). More fundamentally, political stability and rule of Wilfred, 2010). Each intervention is intended to devolve law may accelerate adoption by increasing potential adopters’ resource rights to local governments and communities confidence in receiving the benefits of an innovation. (following official designation), in order to foster resource Geographic context and cultural context also influence stewardship among local residents, ensure residents tangibly adopters’ perceptions of, and interactions with, an innova- benefit from conservation, and, thus, build local support for tion. Relative advantage may vary, for example, based on conservation (Blomley & Ramadhani, 2006; Wilfred, 2010). spatial heterogeneity in physical, biological, or social char- Though each intervention embraces similar principles, they acteristics. Moreover, distance and geographic relief (e.g., demonstrate different rates and patterns of diffusion; to date, 4of9 MASCIA AND MILLS

FIGURE 1 Spatial patterns (a) and temporal trends (b) in the adoption of community-centered conservation interventions in Tanzania. In (b), dates represent the start of the adoption process and village numbers include both registered and unregistered sites for CBFM (blue line), JFM (black line), and WMA (grey line). The dotted grey line represents the ﬁnal registration year for WMAs; these are not available for the other interventions, but we do report the number of CBFM (blue point) and JFM (black point) registered by 2011. Adoption can be a lengthy bureaucratic and resource- intensive process that may take numerous years. Only adoptions where we had the name of the village and the adoption dates are counted. Initial supporting policies for all interventions were established in 1998, although some villages had established these interventions previously. The Forest Policy supported both participatory forest management initiatives, while the Wildlife Management Policy supported the WMA. In all three cases, adoption is by villages, either alone (CBFM) or in conjunction with government agencies and/or tourism companies. WMA data are from Pailler et al. (2015) and World Wildlife Fund (2014); CBFM and JFM data are from Blomley and Iddi (2009)

CBFM has had highest uptake by villages, followed by JFM flicting government approaches to benefit-sharing, and greater and WMAs (Figure 1). levels of corruption relative to JFM and CBFM. Recent (2012) Consistent with diffusion of innovation theory, diffusion changes to WMA policies promise to increase control and of these interventions is correlated with differences in benefits to villagers. To date however, no intervention has innovation characteristics. Supported by Tanzania's Forest consistently demonstrated better social welfare outcomes Policy (UTR 1998), CBFM and JFM focus on lands owned (Pailler, Naidoo, Burgess, Freeman, & Fisher, 2015). by different actors and structure management responsibilities Characteristics of the innovation, adopters, and context differently (Vyamana, 2009). CBFM occurs on village or limited adoption of all three participatory conservation strate- private land, whereas JFM occurs on reserved land owned and gies in Tanzania. The complexity of the three interventions, managed by the state. In CBFM, local residents shoulder most for example, made it difficult for villagers to adopt any of costs but also keep most benefits; government's only role is them without technical assistance from government agencies in monitoring. Under JFM, by contrast, decision-making and or nongovernmental organizations. Moreover, high transac- management costs and benefits are shared, often inequitably, tion costs associated with navigating conflicting government between and among local residents and government (Blomley policies limited intervention trialability and relative advan- & Ramadhani, 2006; Vyamana, 2009). Under the Wildlife tage (Mazur & Stakhanov, 2008). Individuals who success- Policy of Tanzania (1998), WMAs and valuable wildlife fully accessed and held this information often used it to therein are managed jointly by local residents, nongovern- their own advantage (Blomley & Ramadhani, 2006), enhanc- mental organizations, tourism companies, and the Tanzanian ing their personal benefits at the expense of others. Limited state, regional, district and local governments (Schuerholz & information about opportunities related to changes in forest Baldus, 2012; Wilfred, 2010). WMAs take place on village policy, substantial upfront financial costs, extended imple- or private land (Nelson, Nshala, & Rodgers, 2007). Villages mentation times, and time lags between implementation and eager to benefit from tourists hunting within the WMA outcomes were often prohibitively high for impoverished vil- must apply for a hunting block, which, if approved by the lagers (Blomley & Ramadhani, 2006; Robinson & Maganga, government, is also allocated to a tourism company. Villages 2009). can partner with tourism companies but do not select them, limiting their autonomy over the WMA. Relative to JFM 3.2 Locally managed marine areas in the and WMAs, CBFM can provide greater relative advantage to Pacific: same intervention, different contexts villagers: greater autonomy, resource control, and financial benefits (Persha & Blomley, 2009). In particular, the relative Locally managed marine areas (LMMAs) are a conserva- advantage of WMAs has been undermined by conflict over tion intervention with widespread but differential uptake, distribution of future benefits, confusion over policies, con- spreading rapidly in some countries and more slowly in MASCIA AND MILLS 5of9

FIGURE 2 Trends (a) in the adoption of LMMAs by number of adopting villages and (b) LMMA stakeholder dialogue in Fiji. In (a), Fiji is represented by the blue line, Samoa by the gray line, and the Solomon Islands by the black line. LMMA data were from Govan (2009), the LMMA Network and obtained from the Coral Triangle Atlas (https://ctatlas.reefbase.org/mpadatabase.aspx?country=Solomon%20Islands) in 2016. Only LMMAs with defined adoption dates are included within (a) others. LMMAs merge contemporary concepts associated villages were otherwise unable to establish LMMAs (Govan with marine protected areas with longstanding customary et al., 2009). As a result, most LMMA sites are clustered geo- management practices, whereby local residents collectively graphically, reflecting logistical or political factors facilitat- manage an area of inshore ocean waters. From 2001 to 2009, ing support of villages in relatively close proximity (Govan more than 500 villages established LMMAs, encompassing et al., 2009). At a country scale, this dynamic fostered more 12,000 km2 of inshore waters across 15 countries and ter- widespread adoption of LMMAs across Fiji, relative to the ritories (Govan, 2009). Adoption of LMMAs has contin- Solomon Islands. Many nongovernmental organizations are ued throughout the Pacific; in particular, Fiji (n = 434), the based in Fiji, for example, facilitating support to Fijian vil- Solomon Islands1 (n = 174), and Samoa (n = 103)2 have lages. By contrast, LMMA diffusion in the Solomon Islands embraced LMMAs (Govan, 2015; Figure 2). was hindered by limited capacity building and difficulties in LMMA characteristics contributed to widespread adoption effective networking at organizational and community lev- across the Pacific, but also help to explain variation among els (Govan, 2015; Wale, 2006) due to greater distances and nations (Table 1). Relative to other forms of coastal manage- restricted resources (Govan et al., 2009). ment in the Pacific, LMMAs benefit local villagers by enhancing tenure security, community organization, local customs, ecosystem protections, fisheries sustainability, access to information and services, and livelihoods (Govan, 2007; Jupiter, 4 DISCUSSION Cohen, Weeks, Tawake, & Govan, 2014). In Fiji, for example, LMMAs represented a means of reorganizing resource 4.1 Implications for science management around customary tenure systems, which led to Diffusion of innovation theory provides novel insights into widespread interest among local residents. In Samoa, by con- spatial and temporal dynamics of conservation policy and trast, LMMA implementation was driven by the government, practice. Though scientists have previously examined the which encouraged adoption of LMMAs by providing incen- roles of geographic, ecological, demographic, economic, and tives for aquaculture and fishing subsidies (Fa'asili & Taua, political variables (Fox et al., 2012; Miller et al., 2013), 2001). While these incentives initially fostered interest in the conservation literature lacks a theoretical framework and LMMAs, Samoan villagers’ enthusiasm subsequently waned hypotheses to explain these fundamental dynamics (Redford alongside a decline in government investments. et al., 2013). With seven decades of research across disparate The history of LMMAs also highlights the influence of systems (Rogers, 2003), diffusion of innovation theory may social-ecological context upon rates and patterns of diffusion. allow scholars to weave together the scattered research on pat- Cultural and political factors (e.g., desire to revitalize village terns and trends in conservation interventions. authority; recognition of environmental degradation; legal Diffusion of participatory conservation strategies in Tan- recognition and government support for decentralized marine zania and the Pacific Islands is largely consistent with dif- tenure) contributed to the resurgence of community-based fusion of innovation theory. Differential trends in adoption marine resource management across the Pacific (Govan et al., mirrored relative advantage of interventions, particularly the 2009; Johannes, 2002). As with participatory conservation in extent of villager control over access, use, and intervention Tanzania, diffusion of LMMAs across the Pacific was influ- benefits (Blomley & Ramadhani, 2006; Govan, 2015). In both enced by the degree to which external actors assisted local vil- cases, widely adopted conservation interventions reflected lages with planning and implementation; many impoverished 6of9 MASCIA AND MILLS

TABLE 1 Factors that shaped diﬀusion of community-centered conservation interventions in Tanzania and the Paciﬁc LMMA CBFM JFM WMA

Fiji Solomon Islands Samoa Tanzania Characteristics of the innovation Relative advantage + + ○ ○ ○ − Compatibility ++ + + Complexity + + ○ ○ ○ − Trialability + ○ −−− Observability ○ ○ ○ ○ Flexibility ++ ○ + ○ − Characteristics of the actors Existing knowledge ++ ○○○ Nature of social-ecological system Geographic proximity − Political conditions—enabling policies + + + + + ○ Technical assistance + ○ +++ Political conditions—bureaucratic barriers − − − − Explanatory factors based on variables highlighted by diffusion of innovation theory. Ratings are relative to the other case studies examined (across counties for the LMMA and across interventions for Tanzania): “+” represents case-specific conditions that facilitated adoption; “○” represents case-specific conditions for which there is contradicting evidence regarding whether conditions facilitated or hindered adoption, “−” represents case-specific conditions that hindered adoption; blank represents variables for which no information is available. Variables highlighted by diffusion of innovation theory but not discussed within the case literature are not represented; though these variables are not discussed in the literature, they may have played an unreported role in shaping rates and patterns of diffusion of these conservation interventions. and strengthened customary governance systems and, thus, adoption and effectiveness? Last, to what extent are rates were compatible with local values and norms (Babili & and patterns of conservation interventions keeping pace with, Wiersum, 2013; Worldfish 2013). Though policies decentral- outpacing, or lagging behind the scale and scope of biodi- izing resource control were nominally designed to empower versity loss, climate change, and other environmental chal- local actors to manage natural resources (Clarke & Jupiter, lenges? Although conservation researchers have occasionally 2010), rights granted to local villagers varied widely. In Tan- explored these questions, these scattered attempts leave con- zania, diffusion was hindered by policies that provided rela- siderable space for theory-based, policy-relevant, empirical tively less autonomy to local residents (Nelson et al., 2007; research. Nielsen & Treue, 2012). Access to resources, particularly external technical assistance, also shaped rates and patterns of adoption in Tanzania and the Pacific (Govan, Schwarz, & 4.2 Implications for policy Boso, 2011; Lund & Treue, 2008). Patterns emerging from Social scientific insights into the diffusion of conservation our analysis are consistent with the literature on adoption of interventions may empower donors and practitioners to cat- environmental innovations in agriculture, climate policy, and alyze conservation at scale—and to do so at less cost and with analogous contexts (Jordan & Huitema, 2014; Pannell et al., longer-lasting impacts. Traditionally, conservation planning 2006). However, our exploratory analysis precludes compre- has sought to optimize design of protected area networks by hensive testing of diffusion of innovation theory, including the encompassing the most biodiversity at the least possible cost relative importance of individual variables and interactions (Margules & Pressey, 2000), drawing upon data sets provid- among them. ing insights into the viability and opportunity costs of conser- Indeed, theories of innovation diffusion suggest new direc- vation (Knight, Cowling, Difford, & Campbell, 2010). Diffu- tions for biodiversity conservation research. Most fundamen- sion theory highlights additional social variables to consider tally, what are patterns and trends in the adoption of conserva- within conservation planning or, at least, the need to recognize tion policies and practices? How do these patterns and trends that conservation is a dynamic social process with emergent vary among interventions, across geographies, across levels properties associated with adoption of (or resistance to) novel of social organization, and within and among social groups? interventions. What factors explain these dynamics? Do factors that explain Insights from diffusion of innovation theory have clear adoption of new conservation interventions also explain aban- implications for design and implementation of conservation donment of interventions? What is the relationship between interventions. Diffusion is more likely where implementers MASCIA AND MILLS 7of9

FIGURE 3 Pathways for the adoption of innovations (modified from Greenhalgh et al., 2004). Within the blue box are conservation actions associated with different pathways, which range along a continuum from voluntary adoption (unpredictable and self-organizing), to active dissemination (negotiated and enabled), to coercive transfer (ordered and planned) focus on interventions that are simple, readily observable, Conversations with Hugh Govan and participants in the consistent with social beliefs and values, that can be tried and Centre of Excellence for Environmental Decisions Workshop tweaked to fit local context, and with few barriers and costs to in Montpellier, France, in 2015 allowed us to improve this participation. Moreover, diffusion is more likely where imple- manuscript. We thank Hugh Govan, Fiji LMMA Network menters target adopters who have high social status, are well- and the CTI Atlas for providing the LMMAs data for Samoa, connected to the outside world and each other, have auton- Fiji, and Solomon Islands, respectively, Sharon Pailler for omy to innovate, and are competing with others. Last, diffu- WMA data, and Tom Blomley for providing CBFM and JFM sion is most likely where implementers seek out suitable geo- data. graphic, cultural, and policy contexts—and create an enabling policy environment, if not already present. Innovations spread AUTHOR CONTRIBUTIONS through diverse pathways (along a continuum from volun- MBM conceived research; MBM and MM designed research; tary adoption, to active dissemination, to coercive transfer MBM and MM collected data; MBM and MM analyzed data; (e.g., where corporations or governments mandate adoption; MBM and MM wrote and revised manuscript. Figure 3; Dolowitz & Marsh, 1996; Greenhalgh et al., 2004)). Limiting conservation interventions to planned and regulated ENDNOTES strategies, however, may “strangle” emergent conservation interventions by preventing potential adopters from tailoring 1 LMMAs are often referred to as “community-based resource manage- innovations to meet their specific needs. ment” in the Solomon Islands. The history of conservation is marked by fads— 2 LMMAs are also known as “fisheries extension sites” in Samoa. innovations with rapid adoption and rapid abandonment— raising questions about the potential for innovative conservation policies and practices to provide enduring solutions to ORCID environmental challenges (Redford et al., 2013). Diffusion Michael B. Mascia http://orcid.org/0000-0002-9874-9778 of innovation theory provides a novel lens through which to examine rates and patterns associated with adoption of conservation interventions, thus creating the theoretical REFERENCES foundation for catalyzing adoption of enduring interventions Abernethy, K., Bodin, Ö., Olsson, P., Hilly, Z., & Schwarz, A. (2014). that realize their full potential. Given that conservation is one Two steps forward, two steps back: The role of innovation in trans- of the most widespread uses of land and sea globally, and forming towards community-based marine resource management in among the greatest policy challenges of the 21st century, the Solomon Islands. Global Environmental Change, 28, 309–321. stakes are high and potential returns profound. Alcala, A. C., & Russ, G. R. (2006). No-take marine reserves and reef fisheries management in the Philippines: A new people power revo- lution. AMBIO: A Journal of the Human Environment, 35, 245–254. ACKNOWLEDGMENTS Babili, I. H., & Wiersum, F. (2013). Evolution and diversification of com- Roopa Krithivasan and Sarah Wiener provided valu- munity forestry regimes in Babati District, Tanzania. Small-Scale able assistance during initial explorations of this topic. Forestry, 12, 539–557. 8of9 MASCIA AND MILLS

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