Elsevier

Tourism Management

Volume 81, December 2020, 104160
Tourism Management

Monitoring tourists’ specialisation and implementing adaptive governance is necessary to avoid failure of the wildlife tourism commons

https://doi.org/10.1016/j.tourman.2020.104160Get rights and content

Highlights

  • Tourists' level of specialisation is crucial in determining the sustainability of a wildlife tourism destination.

  • There is an interaction between the destination's development stage and the effectiveness of governance structures.

  • No single governance structure is effective in sustainably managing the destination throughout its development cycle.

  • Adaptive governance allows the destination to adapt to change and achieve sustainable outcomes.

Abstract

Wildlife tourism (WT) is an important economic sector globally, which can sustain national and local economies. These activities have been reconceptualised as consumptive because of their impacts on the wildlife, and the problem of managing WT as a common-pool resource issue. We use an individual-based model to simulate the dynamics of a WT destination in different development phases. We then ask if any of the governance structures commonly proposed to solve common pool resource issues are appropriate to sustainably manage a WT destination during its development. The level of specialisation of tourists visiting a destination can influence both the exploitation of the wildlife and the socio-economic success of the industry, and no single governance structure leads to sustainability in every stage of a WT destination lifecycle. Given the dynamics of WT destinations, an adaptive governance framework is crucial to avoid wildlife depletion and economic failure of the industry.

Introduction

Nature recreation is becoming increasingly popular globally (Balmford et al., 2009, 2015). Wildlife recreation is a type of nature recreation that involves interactions with wildlife. Wildlife watching activities were initially welcomed by conservation and environmental organisations as good sustainable alternative use of wildlife compared to other recreational activities such as fishing or hunting (Tisdell & Wilson, 2002). However, in the last two decades, many studies have shown that wildlife watching can have behavioural and physiological impacts on the animals (Amo, López, & Martín, 2006; Beale & Monaghan, 2004; Christiansen, Rasmussen, & Lusseau, 2013; Frid & Dill, 2002; Lusseau, 2003; McClung, Seddon, Massaro, & Setiawan, 2004; Velando & Munilla, 2011), which can affect the individuals’ survival and reproductive rates and result in population-level consequences (Bejder et al., 2006; Christiansen & Lusseau, 2015; McClung et al., 2004; Pirotta, New, Harwood, & Lusseau, 2014; Watson, Bolton, & Monaghan, 2014). The subject literature reports cases of both successful and unsuccessful governance of nature tourism systems. When managed successfully, sustainable nature tourism can alleviate poverty (Ferraro & Hanauer, 2014), stimulate development of infrastructure (Liu et al., 2012), create employment opportunities (Li, Jin, & Shi, 2018) and benefit wildlife conservation (R. C. Buckley, Castley, de Pegas, Mossaz, & Steven, 2012; Lindsey et al., 2014; Wilson, Hayward, & Wilson, 2017). However, when nature tourism systems fail it can lead to declines in wildlife population abundance (Lusseau & Bejder, 2007), reduced effectiveness of protected areas (Reed & Merenlender, 2008) and land-use conflicts with consequences for local populations (Sirima & Backman, 2013; Xi, Zhao, Ge, & Kong, 2014). This has led to a reconceptualization of wildlife tourism as a consumptive activity (James E.S. Higham, Bejder, Allen, Corkeron, & Lusseau, 2016; Meletis & Campbell, 2007) and the problem of how to manage it sustainably as a common pool resource issue (Briassoulis, 2002).

Hardin's (1968) paper introduced the concept of the “tragedy of the commons” to indicate the situation in which users of a common pool resource are trapped in a system of incentives that will encourage them to overexploit the resource and eventually collapse the socioecological system, unless the resource is managed by a central authority or under private property rights regimes. Since then, common pool resource research has documented cases of commons where users have been successful in self-organising and producing sustainable outcomes (Ostrom, 1990; Ostrom, Burger, Field, Norgaard, & Policansky, 1999; Ostrom, Janssen, & Anderies, 2007). We also have numerous examples of attempts to sustainably govern the commons that have failed (Acheson, 2006). Different governance structures have been proposed to manage common pool resources: private property (Lindsey et al., 2014; Muir-Leresche & Nelson, 2000; Wilson et al., 2017), government control (Lovejoy, 2006; Mayer et al., 2018), community-based management and co-management (Conley & Moote, 2003; Lamers, van der Duim, van Wijk, Nthiga, & Visseren-Hamakers, 2014; Sheppard, Moehrenschlager, Mcpherson, & Mason, 2010). Often, these governance solutions are advocated as panaceas, a single solution to every commons. But commons are complex systems and simple solutions are unlikely to be successful (Ostrom et al., 2007). Moving beyond panaceas requires us to navigate each single case study to find a sustainable solution.

Wildlife tourism and recreation systems can be described as made of four main components: the wildlife and the habitat, the tourists, the businesses that make up the tourism offer and the institutions and rules regulating the system. These subsystems are relatively separable, but interact in complex ways to produce outcomes at the system level, which then produce feedback that influences the individual subsystems (Ostrom, 2009). A number of variables have been identified as important to determine the outcomes of socioecological systems (Ostrom, 2009), such as the size and location of the resource system (the destination), the number and growth rate of the resource units (the wildlife) and the socioeconomic attributes of the users (tourists and tour operators). Measuring these variables in real systems provides insights into the social, economic and environmental outcomes of socioecological systems. Wildlife recreation destinations are dynamic, and, as the destination develops, it experiences substantial changes in these system properties that are important in determining if sustainability will be achieved (Ostrom, 2009). As a consequence, governance structures that used to be successful might eventually become inappropriate (Partelow & Nelson, 2018). Nearly 30 years ago, Duffus and Dearden published their conceptual model of non-consumptive wildlife-oriented recreation (Duffus & Dearden, 1990), a framework that brought together Butler's tourism area lifecycle (Butler, 1980), Bryan's tourist specialisation continuum (Bryan, 1977) and the concept of Limits of Acceptable Change – LAC - (Stankey, McCool, & Stokes, 1984). The temporal dynamics of a wildlife tourism destination (Fig. 1) can be described by following the change in the number of tourists visiting it through time. First, the destination goes through an exploration phase, where mostly specialist tourists start discovering the area. This phase is followed by a development phase, characterised by an exponential growth in the number of tourists, infrastructure development at the destination and a shift in tourist typology from specialists to a mixture of specialists and generalists. The last phase of the wildlife tourism destination lifecycle is the consolidation phase, when the number of tourists (mostly generalists) plateaus. Together with these changes in the social and economic dynamics of the wildlife tourism destination, effects on the environment also occur as the number of tourists increases and specialist wildlife watchers are displaced by more generalist tourists, who require more infrastructure and place greater pressure on the environment. After the consolidation phase there are three possible trajectories for the wildlife recreation destination: i) the industry can collapse because of a decline in attractiveness due to overcrowding and environmental degradation; ii) a stagnation phase, where numbers of visitors remain the same; iii) a period of rejuvenation, where the industry changes dramatically allowing a second period of growth (Catlin, Jones, & Jones, 2011; Duffus & Dearden, 1990). Since the publication of this conceptual framework, empirical research has attempted to identify the three stages of development in real tourism case studies and understand how to best manage the destination to minimise permanent effects on the environment and avoid the collapse of the tourism area (Catlin et al., 2011). However, management usually lags behind development and it is likely to intervene only after these effects have started to become obvious (Higham, 2007), and at that point some irreversible consequences might have already started to appear. An ultimate goal is to develop a mechanism to set up institutions and governance structures during the destination's initial phase that can ensure tourism remains sustainable by either avoiding collapse, or finding a stable state in which the destination can remain economically viable without damaging its social and environmental capitals.

Here we aim to investigate the institutions and governance structures that can result in socioeconomically and ecologically sustainable wildlife recreation operations at different stages of the tourism destination life cycle. We define a destination as an area where a number of wildlife watching operations exploit the same wildlife population (Center for Responsible Travel, 2014; Hughes, 2001; Semeniuk, Haider, Cooper, & Rothley, 2010). We build an individual based model (DeAngelis & Mooij, 2005) to simulate a generic wildlife watching destination (Fig. 2), with tourists, tour operators and wildlife agents (Pirotta & Lusseau, 2015) with the aim to determine how changes in the characteristics of tourists, their phenotype thereafter, can influence the sustainability of the destination. Individual-based models are a useful framework to study complex systems as they can show how system level properties emerge from the adaptive behaviour of individuals as well as how the system affects individuals (Railsback, 2001). As we saw, tourist phenotype changes drastically during the life cycle of a destination, yet the effect of these changes in customer phenotype on socioecological sustainability is largely unknown. We test how different tourists’ characteristics and tourism volume trends influence the economic and ecological dynamics of a wildlife watching socioecological system and which governance structure is more likely to achieve a viable industry and the persistence of the targeted wildlife population.

Section snippets

Overview

The model has three main entities: the tourists, the tour operators and the wildlife (Fig. 2). We tested four different governance scenarios: voluntary code of conduct, licensing, user group governance and co-management. For each of these scenarios we simulated socioeconomic and ecological dynamics of the wildlife tourism destination, varying two parameters: type of tourists (3 values: mostly specialists, mostly generalists and mixed) and trend in demand (3 values: increasing, decreasing and

Results

We found that tourist phenotype influenced the socioeconomic and ecological dynamics of the simulated wildlife tourism destination (Fig. 3, Fig. 4). Under any governance scenario and with any trend in demand, a destination visited mainly by generalist tourists will have the highest number of tour operators still in business after 40 years (between 6 and 17 – Fig. S3), while a destination dominated by specialist tourists will only have between 1 and 5 tour operators still in business after 40

Discussion

Looking at the three dimensions of sustainability (social, economic and ecological), we can see that there is no clear winner among the governance strategies tested in these simulations (Fig. 7). Both code of conduct and licensing governance structures can lead to overexploitation when the number of generalist tourists is increasing and the other scenarios can lead to low profits and a very small number of tour operators remaining in the industry. The main driver of sustainability was the type

Limitations

As any model, the simulations presented in this study represent a simplified version of a real wildlife tourism system. From this simplification a number of limitations arise that need to be acknowledged and discussed.

Many components of real wildlife tourism systems have not been addressed in this study. We did not consider the impact of differences in some of the variables identified by Ostrom (2009) that can affect sustainability of socioecological systems, for example the focal species. We

Conclusions

The expectations and preferences of tourists have a strong influence on the sustainability of a wildlife tourism destination. The dominating tourist phenotype in a destination can influence both the exploitation of the environment and the socio-economic success of the industry. We did not find a strong effect of governance type on the outcomes of the destination, with no governance structure appearing more successful than the others in every situation. What we find instead is that the best

Author contribution

All authors contributed to conceiving the idea and designing the model. FM and DL planned and carried out the simulations. All authors contributed to the interpretation of the results. FM led the writing of the manuscript. All authors provided critical feedback and helped shape the research, analysis and manuscript.

Data statement

All the scripts necessary to reproduce the results presented in this paper are available at Mancini, F. (2018) WildlifeWatchingIBM. https://doi.org/10.5281/zenodo.1443307. https://zenodo.org/account/settings/github/repository/FrancescaMancini/WildlifeWatchingIBM.

Declaration of competing interest

None.

Acknowledgments

This work was funded by the University of Aberdeen, through MASTS (the Marine Alliance for Science and Technology for Scotland), and Scottish Natural Heritage (SNH), through a Dominic Counsell studentship, and their support is gratefully acknowledged. The authors would also like to thank Alex Douglas for allowing us to run the simulations on the Catling computer cluster.

Francesca Mancini: Francesca is an early-career researcher and an ecological modeller at the Centre for Ecology & Hydrology. Francesca completed her bachelor's degree in Biological Sciences at La Sapienza University of Rome. She obtained an MRes degree in Applied Marine and Fisheries Ecology at the University of Aberdeen, where she also completed a PhD on sustainable management of wildlife tourism.

References (93)

  • K.X. Li et al.

    Tourism as an important impetus to promoting economic growth: A critical review

    Tourism Management Perspectives

    (2018)
  • T.E. Lovejoy

    Protected areas: A prism for a changing world

    Trends in Ecology & Evolution

    (2006)
  • F. Mancini et al.

    Using qualitative models to define sustainable management for the commons in data poor conditions

    Environmental Science & Policy

    (2017)
  • M. Mayer et al.

    The nexus between governance and the economic impact of whale-watching. The case of the coastal lagoons in the El Vizcaíno Biosphere Reserve, Baja California, Mexico

    Ocean & Coastal Management

    (2018)
  • M.R. McClung et al.

    Nature-based tourism impacts on yellow-eyed penguins megadyptes antipodes: Does unregulated visitor access affect fledging weight and juvenile survival?

    Biological Conservation

    (2004)
  • J. Morais et al.

    Research gaps of coral ecology in a changing world

    Marine Environmental Research

    (2018)
  • N. Muboko et al.

    Illegal hunting and protected areas: Tourist perceptions on wild animal poisoning in Hwange National Park, Zimbabwe

    Tourism Management

    (2016)
  • C.N. Mutanga et al.

    Travel motivation and tourist satisfaction with wildlife tourism experiences in Gonarezhou and Matusadona National Parks, Zimbabwe

    Journal of Outdoor Recreation and Tourism

    (2017)
  • E. Pirotta et al.

    Activities, motivations and disturbance: An agent-based model of bottlenose dolphin behavioral dynamics and interactions with tourism in Doubtful Sound, New Zealand

    Ecological Modelling

    (2014)
  • S.F. Railsback

    Concepts from complex adaptive systems as a framework for individual-based modelling

    Ecological Modelling

    (2001)
  • C.A.D. Semeniuk et al.

    A linked model of animal ecology and human behavior for the management of wildlife tourism

    Ecological Modelling

    (2010)
  • A. Velando et al.

    Disturbance to a foraging seabird by sea-based tourism: Implications for reserve management in marine protected areas

    Biological Conservation

    (2011)
  • H. Watson et al.

    Out of sight but not out of harm's way: Human disturbance reduces reproductive success of a cavity-nesting seabird

    Biological Conservation

    (2014)
  • J. Xi et al.

    Changes in land use of a village driven by over 25 years of tourism: The case of Gougezhuang village, China

    Land Use Policy

    (2014)
  • Q. Ye et al.

    The impact of online user reviews on hotel room sales

    International Journal of Hospitality Management

    (2009)
  • J.M. Acheson

    Institutional failure in resource management

    Annual Review of Anthropology

    (2006)
  • J.M. Anderies et al.

    Panaceas, uncertainty, and the robust control framework in sustainability science

    Proceedings of the National Academy of Sciences of the United States of America

    (2007)
  • C.W. Armstrong et al.

    Optimal allocation of TAC and the implications of implementing an ITQ management system for the north-East Arctic Cod

    Land Economics

    (2001)
  • A. Balmford et al.

    A global perspective on trends in nature-based tourism

    PLoS Biology

    (2009)
  • A. Balmford et al.

    Walk on the wild side: Estimating the global magnitude of visits to protected areas

    PLoS Biology

    (2015)
  • C.M. Beale et al.

    Human disturbance: People as predation-free predators?

    Journal of Applied Ecology

    (2004)
  • L. Bejder et al.

    Decline in relative abundance of bottlenose dolphins exposed to long-term disturbance

    Conservation Biology

    (2006)
  • H. Bryan

    Leisure value systems and recreational specialization: The case of trout fishermen

    Leisure Research

    (1977)
  • R.C. Buckley et al.

    A population accounting approach to assess tourism contributions to conservation of IUCN-redlisted mammal species

    PloS One

    (2012)
  • R.W. Butler

    The concept of a tourist area cycle of evolution: Implications for management of resources

    Canadian Geographer

    (1980)
  • D.W. Cash et al.

    Knowledge systems for sustainable development

    Proceedings of the National Academy of Sciences of the United States of America

    (2003)
  • J. Catlin et al.

    Consolidation in a wildlife tourism industry: The changing impact of whale shark tourist expenditure in the Ningaloo coast region

    International Journal of Tourism Research

    (2010)
  • Economic impact of bear viewing and bear hunting in the great bear rainforest of British Columbia

    (2014)
  • F. Christiansen et al.

    Linking behavior to vital rates to measure the effects of non-lethal disturbance on wildlife

    Conservation Letters

    (2015)
  • F. Christiansen et al.

    Whale watching disrupts feeding activities of minke whales on a feeding ground

    Marine Ecology Progress Series

    (2013)
  • A. Conley et al.

    Evaluating collaborative natural resource management

    Society & Natural Resources

    (2003)
  • B. Davis et al.

    The value of tourism expenditure related to the East of Scotland Bottlenose dolphin population

    (2010)
  • D.L. DeAngelis et al.

    Individual-based modeling of ecological and evolutionary processes

    Annual Review of Ecology, Evolution and Systematics

    (2005)
  • T. Dietz et al.

    The struggle to govern the commons

    Science

    (2003)
  • K. Dimmock et al.

    Stakeholders, industry knowledge and adaptive management in the Australian whale-watching industry

    Journal of Sustainable Tourism

    (2014)
  • On the conservation of natural habitats and of wild fauna and flora

    Official Journal of the European Communities, L 269(May 1992

    (1992)
  • Cited by (11)

    • Segmented importance-performance analysis in whale-watching: Reconciling ocean coastal tourism with whale preservation

      2023, Ocean and Coastal Management
      Citation Excerpt :

      Following up on previous research about market segmentation in marine wildlife tourism, the results of this study confirm that there are tourists with a specialised interest in wildlife, as well as tourists with more recreational interests (Bentz et al., 2016b; Duffus and Dearden, 1990; Moscardo, 2000; Tkaczynski and Rundle-Thiele, 2018). However, there is scarce research to date on how tourist segmentation might contribute to more meaningful management guidelines for the sustainability of whale-watching tourism (Bentz et al., 2016b; Bruyere et al., 2002; Caber et al., 2012; Kruger et al., 2018; Lai and Hitchcock, 2015; Malcolm and Duffus, 2008; Mancini et al., 2020; Phan and Schott, 2019). Furthermore, product segmentation has rarely provided useful insights for firms that would help to meet the preferences of the different groups of consumers.

    • Innovative internet of things (IoT) for sustainable tourism

      2022, Handbook of Innovation for Sustainable Tourism
    View all citing articles on Scopus

    Francesca Mancini: Francesca is an early-career researcher and an ecological modeller at the Centre for Ecology & Hydrology. Francesca completed her bachelor's degree in Biological Sciences at La Sapienza University of Rome. She obtained an MRes degree in Applied Marine and Fisheries Ecology at the University of Aberdeen, where she also completed a PhD on sustainable management of wildlife tourism.

    Ben Leyshon: Ben has a BSc in Marine and Freshwater Biology, University of London and an MSc in Rural Resource Management University College of North Wales. For 27 years Ben has worked for Scottish Natural Heritage and he is Operations Manager for the Scottish Highlands. Ben has a lead on marine issues in the north of Scotland and in particular the Moray Firth. This has involved working with port and harbour authorities, the energy sector, fisheries, recreation and tourism groups. Ben is actively involved in marine planning and policy and has represented SNH on multiple marine partnerships and management groups.

    Fiona Manson: Dr Fiona Manson is a marine adviser at Scottish Natural Heritage (SNH). Fiona provides advice on the conservation of marine wildlife in Scotland, covering a range of sectors including marine tourism. She leads on the development and promotion of the Scottish Marine Wildlife Watching Code. Prior to working at SNH, Fiona has worked in fisheries research and aquaculture in Scotland, Australia and Iceland.

    George M. Coghill: George is SICSA Chair in System Modelling and Professor of Computing Science at the University of Aberdeen. His main research interests are in Model-based Systems & Qualitative Reasoning, Bio-inspired Computing, and Philosophy of Information & Modelling. His research is very interdisciplinary and he has applied it to areas across a spectrum from biology and medicine, to music and sociology. He is a Fellow of the Institution of Engineering and Technology.

    David Lusseau: David is Professor of Behavioural Biology at the University of Aberdeen. He works at the intersection of life, formal, and social sciences to understand how individuals make decisions when uncertain and what the consequences of those decisions are for their lives and their contributions to others. He obtained his PhD at the University of Otago in 2003. He was elected Fellow of the Royal Statistical Society in 2009, the Royal Society of Biology in 2016, and member of the Young Academy of Scotland in 2011. He currently serves on IUCN Species Survival Commission and IUCN Sustainable Use and Livelihoods Specialist Group.

    1

    Present address: UK Centre for Ecology & Hydrology, Maclean Building, Crowmarsh Gifford, Wallingford, OX10 8BB, UK.

    View full text