scholarly journals Operationalizing vulnerability for social–ecological integration in conservation and natural resource management

2019 ◽  
Vol 13 (1) ◽  
Author(s):  
Lauric Thiault ◽  
Stefan Gelcich ◽  
Nadine Marshall ◽  
Paul Marshall ◽  
Frédérique Chlous ◽  
...  
2017 ◽  
Vol 18 (2) ◽  
pp. 581-592 ◽  
Author(s):  
Maria del Mar Delgado-Serrano ◽  
Elisa Oteros-Rozas ◽  
Isabel Ruiz-Mallén ◽  
Diana Calvo-Boyero ◽  
Cesar Enrique Ortiz-Guerrero ◽  
...  

2015 ◽  
Vol 20 (4) ◽  
Author(s):  
Maria del Mar Delgado-Serrano ◽  
Elisa Oteros-Rozas ◽  
Pieter Vanwildemeersch ◽  
César Ortíz-Guerrero ◽  
Silvia London ◽  
...  

2019 ◽  
Vol 15 (2) ◽  
pp. 555-567 ◽  
Author(s):  
Stuart Cottrell ◽  
Katherine M. Mattor ◽  
Jesse L. Morris ◽  
Christopher J. Fettig ◽  
Pavlina McGrady ◽  
...  

2019 ◽  
Vol 21 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Daniel K. Okamoto ◽  
Melissa R. Poe ◽  
Tessa B. Francis ◽  
André E. Punt ◽  
Phillip S. Levin ◽  
...  

2021 ◽  
Author(s):  
Jeroen Minderman ◽  
A. Bradley Duthie ◽  
Isabel L. Jones ◽  
Laura Thomas-Walters ◽  
Adrian Bach ◽  
...  

Models have become indispensable tools in conservation science in the face of increasingly rapid loss of biodiversity through anthropogenic habitat loss and natural resource exploitation. In addition to their ecological components, accurately representing human decision-making processes in such models is vital to maximise their utility. This can be problematic as modelling complexity increases, making them challenging to communicate and parameterise. Games have a long history of being used as science communication tools, but are less widely used as data collection tools, particularly in videogame form. We propose a novel approach to (1) aid communication of complex social-ecological models, and (2) "gamesource" human decision-making data, by explicitly casting an existing modelling framework as an interactive videogame. We present players with a natural resource management game as a front-end to a social-ecological modelling framework (Generalised Management Strategy Evaluation, GMSE). Players' actions replace a model algorithm making management decisions about a population of wild animals, which graze on crops and can thus lower agricultural yield. A number of non-player agents (farmers) respond through modelled algorithms to the player's management, taking actions that may affect their crop yield as well as the animal population. Players are asked to set their own management goal (e.g. maintain the animal population at a certain level or improve yield) and make decisions accordingly. Trial players were also asked to provide any feedback on both gameplay and purpose. We demonstrate the utility of this approach by collecting and analysing game play data from a sample of trial plays, in which we systematically vary two model parameters, and allowing trial players to interact with the model through the game interface. As an illustration, we show how variations in land ownership and the number of farmers in the system affects decision-making patterns as well as population trajectories (extinction probabilities). We discuss the potential and limitations of this model-game approach in the light of trial player feedback received. In particular, we highlight how a common concern about the game framework (perceived lack of "realism" or relevance to a specific context) are actually criticisms of the underlying model, as opposed to the game itself. This further highlights both the parallels between games and models, as well as the utility of model-games to aid in communicating complex models. We conclude that videogames may be an effective tool for conservation and natural resource management, and that although they provide a promising means to collect data on human decision-making, it is vital to carefully consider both external validity and potential biases when doing so.


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