Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia
ilustraciones, mapas
- Autores:
-
Berrio Giraldo, Linda Ivette
- Tipo de recurso:
- Doctoral thesis
- Fecha de publicación:
- 2020
- Institución:
- Universidad Nacional de Colombia
- Repositorio:
- Universidad Nacional de Colombia
- Idioma:
- spa
- OAI Identifier:
- oai:repositorio.unal.edu.co:unal/79646
- Palabra clave:
- 620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica
Ecosistemas
Cuencas hidrográficas - Colombia
Sistemas socio-ecológicos
Modelación integrada
Enfoques de modelación
Sostenibilidad
Escenarios
Interacciones en doble vía
Socio-ecological systems
Integrated modeling
Modeling approaches
Sustainability
Scenarios
Two-way interactions
- Rights
- openAccess
- License
- Atribución-NoComercial-SinDerivadas 4.0 Internacional
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UNACIONAL2 |
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Universidad Nacional de Colombia |
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dc.title.spa.fl_str_mv |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
dc.title.translated.eng.fl_str_mv |
Dynamics of socio-ecological systems in mountain basin, Colombia |
title |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
spellingShingle |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia 620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica Ecosistemas Cuencas hidrográficas - Colombia Sistemas socio-ecológicos Modelación integrada Enfoques de modelación Sostenibilidad Escenarios Interacciones en doble vía Socio-ecological systems Integrated modeling Modeling approaches Sustainability Scenarios Two-way interactions |
title_short |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
title_full |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
title_fullStr |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
title_full_unstemmed |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
title_sort |
Dinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, Colombia |
dc.creator.fl_str_mv |
Berrio Giraldo, Linda Ivette |
dc.contributor.advisor.none.fl_str_mv |
Villegas Palacio, Clara Inés Arango Aramburo, Santiago |
dc.contributor.author.none.fl_str_mv |
Berrio Giraldo, Linda Ivette |
dc.subject.ddc.spa.fl_str_mv |
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica |
topic |
620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulica Ecosistemas Cuencas hidrográficas - Colombia Sistemas socio-ecológicos Modelación integrada Enfoques de modelación Sostenibilidad Escenarios Interacciones en doble vía Socio-ecological systems Integrated modeling Modeling approaches Sustainability Scenarios Two-way interactions |
dc.subject.lemb.none.fl_str_mv |
Ecosistemas Cuencas hidrográficas - Colombia |
dc.subject.proposal.spa.fl_str_mv |
Sistemas socio-ecológicos Modelación integrada Enfoques de modelación Sostenibilidad Escenarios Interacciones en doble vía |
dc.subject.proposal.eng.fl_str_mv |
Socio-ecological systems Integrated modeling Modeling approaches Sustainability Scenarios Two-way interactions |
description |
ilustraciones, mapas |
publishDate |
2020 |
dc.date.issued.none.fl_str_mv |
2020-07-30 |
dc.date.accessioned.none.fl_str_mv |
2021-06-18T14:47:59Z |
dc.date.available.none.fl_str_mv |
2021-06-18T14:47:59Z |
dc.type.spa.fl_str_mv |
Trabajo de grado - Doctorado |
dc.type.driver.spa.fl_str_mv |
info:eu-repo/semantics/doctoralThesis |
dc.type.version.spa.fl_str_mv |
info:eu-repo/semantics/acceptedVersion |
dc.type.coar.spa.fl_str_mv |
http://purl.org/coar/resource_type/c_db06 |
dc.type.content.spa.fl_str_mv |
Text |
dc.type.redcol.spa.fl_str_mv |
http://purl.org/redcol/resource_type/TD |
format |
http://purl.org/coar/resource_type/c_db06 |
status_str |
acceptedVersion |
dc.identifier.uri.none.fl_str_mv |
https://repositorio.unal.edu.co/handle/unal/79646 |
dc.identifier.instname.spa.fl_str_mv |
Universidad Nacional de Colombia |
dc.identifier.reponame.spa.fl_str_mv |
Repositorio Institucional Universidad Nacional de Colombia |
dc.identifier.repourl.spa.fl_str_mv |
https://repositorio.unal.edu.co/ |
url |
https://repositorio.unal.edu.co/handle/unal/79646 https://repositorio.unal.edu.co/ |
identifier_str_mv |
Universidad Nacional de Colombia Repositorio Institucional Universidad Nacional de Colombia |
dc.language.iso.spa.fl_str_mv |
spa |
language |
spa |
dc.relation.references.spa.fl_str_mv |
Abram, J.J., Dyke, J.G., 2018. Structural Loop Analysis of Complex Ecological Systems. Ecol. Econ. 154, 333–342. https://doi.org/10.1016/j.ecolecon.2018.08.011 Ahmad, S., Prashar, D., 2010. Evaluating Municipal Water Conservation Policies Using a Dynamic Simulation Model. Water Resour Manag. 24, 3371–3395. https://doi.org/10.1007/s11269-010-9611-2 Alexander, S.M., Andrachuk, M., Armitage, D., 2016. Navigating governance networks for community-based conservation. Front. Ecol. Environ. 14, 155–164. https://doi.org/10.1002/fee.1251 An, L., 2012. Modeling human decisions in coupled human and natural systems: Review of agent-based models. Ecol. Modell. 229, 25–36. https://doi.org/10.1016/j.ecolmodel.2011.07.010 Anderies, J.M., Janssen, M. a, Ostrom, E., 2004. A Framework to Analyze the Robustness of Social-Ecological Systems from an Institutional Perspective. Ecol. Soc. 9, 1–18. https://doi.org/18 Anselme, B., Bousquet, F., Lyet, A., Etienne, M., Fady, B., Le Page, C., 2010. Modelling of spatial dynamics and biodiversity conservation on Lure mountain (France). Environ. Model. Softw. 25, 1385–1398. https://doi.org/10.1016/j.envsoft.2009.09.001 Anwar, S.M., Jeanneret, C.A., Parrott, L., Marceau, D.J., 2007. Conceptualization and implementation of a multi-agent model to simulate whale-watching tours in the St. Lawrence Estuary in Quebec, Canada. Environ. Model. Softw. 22, 1775–1787. https://doi.org/10.1016/j.envsoft.2007.02.007 Aumann, C.A., 2006. A methodology for developing simulation models of complex systems. https://doi.org/10.1016/j.ecolmodel.2006.11.005 Bagstad, K.J., Johnson, G.W., Voigt, B., Villa, F., 2013. Spatial dynamics of ecosystem service flows: A comprehensive approach to quantifying actual services. Ecosyst. Serv. 4, 117–125. https://doi.org/10.1016/j.ecoser.2012.07.012 Baños-González, I., Martínez-Fernández, J., Esteve-Selma, M.Á., 2013. Dynamic simulation of socio-ecological Systems: sustainability in Biosphere Reserves. Ecosistemas 22, 74–83. https://doi.org/10.7818/ecos.2013.22-3.11 Barlas, Y., 1996. Formal aspects of model validity and validation in system dynamics. Syst. Dyn. Rev. 12, 183–210. https://doi.org/10.1002/(SICI)1099-1727(199623)12:3<183::AID-SDR103>3.0.CO;2-4 Barnaud, C., Bousquet, F., Trebuil, G., 2008. Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand. https://doi.org/10.1016/j.ecolecon.2007.10.022 BenDor, T.K., Kaza, N., 2012. A theory of spatial system archetypes. Syst. Dyn. Rev. 28, 109–130. https://doi.org/10.1002/sdr.1470 Berrouet, L., Villegas-Palacio, C., Botero, V., 2019. A social vulnerability index to changes in ecosystem services provision at local scale: A methodological approach. Environ. Sci. Policy 93, 158–171. Berrouet, L.M., 2018. Vulnerabilidad de sistemas sociales frente a la modificación de servicios ecosistémicos en cuencas hidrográficas de media montaña. Universidad Nacional de Colombia Sede Medellín. Berrouet, L.M., Machado, J., Villegas-Palacio, C., 2018. Vulnerability of socio—ecological systems: A conceptual Framework. Ecol. Indic. 84, 632–647. https://doi.org/10.1016/j.ecolind.2017.07.051 Bodin, O., Tengo, M., 2012. Disentangling intangible social-ecological systems. Glob. Environ. Chang. 22, 430–439. https://doi.org/10.1016/j.gloenvcha.2012.01.005 Bolognesi, T., Ciancia, V., 2017. Exploring nominal cellular automata. J. Log. Algebr. Methods Program. 93, 23–41. https://doi.org/10.1016/J.JLAMP.2017.08.001 Bousquet, F., Le Page, C., 2004. Multi-agent simulations and ecosystem management: A review. Ecol. Modell. 176, 313–332. https://doi.org/10.1016/j.ecolmodel.2004.01.011 Chan, K.M.A., Guerry, A.D., Balvanera, P., Klain, S., Satterfield, T., Basurto, X., Bostrom, A., Chuenpagdee, R., Gould, R., Halpern, B.S., Hannahs, N., Levine, J., Norton, B., Ruckelshaus, M., Russell, R., Tam, J., Woodside, U., 2012. Where are Cultural and Social in Ecosystem Services? A Framework for Constructive Engagement. Bioscience 62, 744–756. https://doi.org/10.1525/bio.2012.62.8.7 Change, I.P. on C., 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of hte Intergovernmental Panel on Climate Change. Chen, Y., Bakker, M.M., Ligtenberg, A., Bregt, A.K., 2016. How are feedbacks represented in land models? Land 5, 29. https://doi.org/10.3390/land5030029 Ciftcioglu, G.C., 2017. Assessment of the resilience of socio-ecological production landscapes and seascapes: A case study from Lefke Region of North Cyprus. Ecol. Indic. 73, 128–138. https://doi.org/10.1016/j.ecolind.2016.09.036 Claessens, L., Schoorl, J.M., Verburg, P.H., Geraedts, L., Veldkamp, A., 2009. Modelling interactions and feedback mechanisms between land use change and landscape processes. Agric. Ecosyst. Environ. 129, 157–170. https://doi.org/10.1016/j.agee.2008.08.008 Collins, Scott L, Carpenter, S.R., Swinton, S.M., Orenstein, D.E., Childers, D.L., Gragson, T.L., Grimm, N.B., Grove, J.M., Harlan, S.L., Kaye, J.P., Knapp, A.K., Kofinas, G.P., Magnuson, J.J., McDowell, W.H., Melack, J.M., Ogden, L.A., Robertson, G.P., Smith, M.D., Whitmer, A.C., 2011. An integrated conceptual framework for long-term social–ecological research. Front. Ecol. Environ. 9, 351–357. https://doi.org/10.1890/100068 Colomer, M.À., Montori, A., García, E., Fondevilla, C., 2014. Using a bioinspired model to determine the extinction risk of Calotriton asper populations as a result of an increase in extreme rainfall in a scenario of climatic change. Ecol. Modell. 281, 1–14. https://doi.org/10.1016/j.ecolmodel.2014.02.018 Cooper, G.S., Dearing, J.A., 2019. Modelling future safe and just operating spaces in regional social-ecological systems. Sci. Total Environ. 651, 2105–2117. https://doi.org/10.1016/j.scitotenv.2018.10.118 Coyle, R.G., 1996. System dynamics modelling : a practical approach. Chapman & Hall. David, N., 2013. Validating Simulations. Springer, Berlin, Heidelberg, pp. 135–171. https://doi.org/10.1007/978-3-540-93813-2_8 Davis, J.P., Eisenhardt, K.M., Bingham, C.B., 2007. Developing theory through simulation methods. Acad. Manag. Rev 32, 480–499. Díaz, S., Demissew, S., Carabias, J., Joly, C., Lonsdale, M., Ash, N., Larigauderie, A., Adhikari, J.R., Arico, S., Báldi, A., Bartuska, A., Baste, I.A., Bilgin, A., Brondizio, E., Chan, K.M.A., Figueroa, V.E., Duraiappah, A., Fischer, M., Hill, R., Koetz, T., Leadley, P., Lyver, P., Mace, G.M., Martin-Lopez, B., Okumura, M., Pacheco, D., Pascual, U., Pérez, E.S., Reyers, B., Roth, E., Saito, O., Scholes, R.J., Sharma, N., Tallis, H., Thaman, R., Watson, R., Yahara, T., Hamid, Z.A., Akosim, C., Al-Hafedh, Y., Allahverdiyev, R., Amankwah, E., Asah, T.S., Asfaw, Z., Bartus, G., Brooks, A.L., Caillaux, J., Dalle, G., Darnaedi, D., Driver, A., Erpul, G., Escobar-Eyzaguirre, P., Failler, P., Fouda, A.M.M., Fu, B., Gundimeda, H., Hashimoto, S., Homer, F., Lavorel, S., Lichtenstein, G., Mala, W.A., Mandivenyi, W., Matczak, P., Mbizvo, C., Mehrdadi, M., Metzger, J.P., Mikissa, J.B., Moller, H., Mooney, H.A., Mumby, P., Nagendra, H., Nesshover, C., Oteng-Yeboah, A.A., Pataki, G., Roué, M., Rubis, J., Schultz, M., Smith, P., Sumaila, R., Takeuchi, K., Thomas, S., Verma, M., Yeo-Chang, Y., Zlatanova, D., 2015. The IPBES Conceptual Framework - connecting nature and people. Curr. Opin. Environ. Sustain. 14, 1–16. https://doi.org/10.1016/j.cosust.2014.11.002 Duespohl, M., Frank, S., Doell, P., 2012. A Review of Bayesian Networks as a Participatory Modeling Approach in Support of Sustainable Environmental Management. J. Sustain. Dev. 5, 0–18. https://doi.org/10.5539/jsd.v5n12p1 Duncan, C., Thompson, J.R., Pettorelli, N., 2015. The quest for a mechanistic understanding of biodiversity–ecosystem services relationships. Proc. R. Soc. B Biol. Sci. 282, 20151348. https://doi.org/10.1098/rspb.2015.1348 Elmahdi, A.., McFarlane, D.., 2010. DSS and MAF (multi-agencies framework) for sustainable water management, Modelling for Environment’s Sake: Proceedings of the 5th Biennial Conference of the International Environmental Modelling and Software Society, iEMSs 2010. Ottawa. Elsawah, S., Mclucas, A., Mazanov, J., 2015. Communicating About Water Issues in Australia: A Simulation/Gaming Approach. Simul. Gaming 46, 713–741. https://doi.org/10.1177/1046878115580410 Elsawah, S., Pierce, S.A., Hamilton, S.H., van Delden, H., Haase, D., Elmahdi, A., Jakeman, A.J., 2017. An overview of the system dynamics process for integrated modelling of socio-ecological systems: Lessons on good modelling practice from five case studies. Environ. Model. Softw. 93, 127–145. https://doi.org/10.1016/j.envsoft.2017.03.001 Filatova, T., Verburg, P.H., Parker, D.C., Stannard, C.A., 2013. Spatial agent-based models for socio-ecological systems: Challenges and prospects. Environ. Model. Softw. 45, 1–7. https://doi.org/10.1016/j.envsoft.2013.03.017 Fondevilla, C., Àngels Colomer, M., Fillat, F., Tappeiner, U., 2016. Using a new PDP modelling approach for land-use and land-cover change predictions: A case study in the Stubai Valley (Central Alps). Ecol. Modell. 322, 101–114. https://doi.org/10.1016/j.ecolmodel.2015.11.016 Forrester, J., 2009. Some basic concepts in system dynamics. Sloan Sch. Manag. … 1–17. Forrester, J.W., 1971. Counterintuitive behaviour of social systems. Theory Decis. 2, 109–140. Gaines, S.D., Dee, L.E., Allesina, S., Bonn, A., Eklöf, A., Gaines, S.D., Hines, J., Jacob, U., Mcdonald-madden, E., Possingham, H., 2017. Operationalizing Network Theory for Ecosystem Service Assessments Operationalizing Network Theory for Ecosystem Service Assessments. Trends Ecol. Evol. 32, 118–130. https://doi.org/10.1016/j.tree.2016.10.011 Gotts, N.M., van Voorn, G.A.K., Polhill, J.G., Jong, E. de, Edmonds, B., Hofstede, G.J., Meyer, R., 2018. Agent-based modelling of socio-ecological systems: Models, projects and ontologies. Ecol. Complex. https://doi.org/10.1016/j.ecocom.2018.07.007 Halmy, M.W.A., Gessler, P.E., Hicke, J.A., Salem, B.B., 2015. Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Appl. Geogr. 63, 101–112. https://doi.org/10.1016/j.apgeog.2015.06.015 Hamilton, S.H., Elsawah, S., Guillaume, J.H.A., Jakeman, A.J., Pierce, S.A., 2015. Integrated assessment and modelling: Overview and synthesis of salient dimensions. https://doi.org/10.1016/j.envsoft.2014.12.005 Hare, M., Deadman, P., 2004. Further towards a taxonomy of agent-based simulation models in environmental management. Math. Comput. Simul. 64, 25–40. https://doi.org/10.1016/S0378-4754(03)00118-6 Hoshino, E., van Putten, I., Girsang, W., Resosudarmo, B.P., Yamazaki, S., 2016. A Bayesian belief network model for community-based coastal resource management in the Kei Islands, Indonesia. Ecol. Soc. 21, art16. https://doi.org/10.5751/ES-08285-210216 Howick, S., Eden, C., Ackermann, F., Williams, T., 2007. Building confidence in models for multiple audiences: The modelling cascade. https://doi.org/10.1016/j.ejor.2007.02.027 Ilachinski, A., 2001. Cellular Automata. A discrete Universe. WORLD SCIENTIFIC. https://doi.org/10.1142/4702 Jakeman, A.J., Letcher, R.A., Norton, J.P., Au, A.J., Jakeman, ), 2006. Ten iterative steps in development and evaluation of environmental models. Environ. Model. Softw. 21, 602–614. https://doi.org/10.1016/j.envsoft.2006.01.004 Kelly, R.A.. B., Jakeman, A.J.., Barreteau, O.., Borsuk, M.E.., ElSawah, S.., Hamilton, S.H.., Henriksen, H.J.., Kuikka, S.., Maier, H.R.., Rizzoli, A.E.., van Delden, H.. I., Voinov, A.A.., 2013. Selecting among five common modelling approaches for integrated environmental assessment and management. Environ. Model. Softw. 47, 159–181. https://doi.org/10.1016/j.envsoft.2013.05.005 Kim, B.S., Kim, T.G., 2019. Cooperation of simulation and data model for performance analysis of complex systems. Int. J. Simul. Model. 18, 608–619. https://doi.org/10.2507/IJSIMM18(4)491 Kok, K., 2009. The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development, with an example from Brazil. Glob. Environ. Chang. 19, 122–133. https://doi.org/10.1016/j.gloenvcha.2008.08.003 Korb, K.B., Nicholson, A.E., 2011. Bayesian artificial intelligence. CRC Press. Kramer, D.B., Hartter, J., Boag, A.E., Jain, M., Stevens, K., Nicholas, K.A., McConnell, W.J., Liu, J., 2017. Top 40 questions in coupled human and natural systems (CHANS) research. Ecol. Soc. 22, art44. https://doi.org/10.5751/ES-09429-220244 Lambin, E.F., Meyfroidt, P., 2010. Land use transitions: Socio-ecological feedback versus socio-economic change. Land use policy 27, 108–118. https://doi.org/10.1016/j.landusepol.2009.09.003 Lauf, S., Haase, D., Hostert, P., Lakes, T., Kleinschmit, B., 2012. Uncovering land-use dynamics driven by human decision-making - A combined model approach using cellular automata and system dynamics. Environ. Model. Softw. 27–28, 71–82. https://doi.org/10.1016/j.envsoft.2011.09.005 Levontin, P., Kulmala, S., Haapasaari, P., Kuikka, S., 2011. Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon. ICES J. Mar. Sci. 68, 632–638. https://doi.org/10.1093/icesjms/fsr004 Liu, J., Dietz, T., Carpenter, S.R., Alberti, M., Folke, C., Moran, E., Pell, A.N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C.L., Schneider, S.H., Taylor, W.W., 2007. Complexity of Coupled Human and Natural Systems. Science (80-. ). 317, 1513–1516. https://doi.org/10.1126/science.1144004 Liu, Y., Gupta, H., Springer, E., Wagener, T., 2008. Linking science with environmental decision making: Experiences from an integrated modeling approach to supporting sustainable water resources management. https://doi.org/10.1016/j.envsoft.2007.10.007 Liu, Y., Long, H., 2016. Land use transitions and their dynamic mechanism: The case of the Huang-Huai-Hai Plain. J. Geogr. Sci. 26, 515–530. https://doi.org/10.1007/s11442-016-1283-2 López-Carr, D., Davis, J., Jankowska, M.M., Grant, L., López-Carr, A.C., Clark, M., 2012. Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala. Ecol. Modell. 229, 64–75. https://doi.org/10.1016/j.ecolmodel.2011.08.020 Luna-Reyes, L.F., Andersen, D.L., 2003. Collecting and analyzing qualitative data for system dynamics: Methods and models. Syst. Dyn. Rev. 19, 271–296. https://doi.org/10.1002/sdr.280 Martín-López, B., García-Llorente, M., Palomo, I., Montes, C., García-Nieto, A.P., Quintas-Soriano, C., 2014. Collaborative mapping of ecosystem services: The role of stakeholders׳ profiles. Ecosyst. Serv. 13, 141–152. https://doi.org/10.1016/j.ecoser.2014.11.006 Martín-López, B., Gómez-Baggethun, E., Montes, C., 2009. Un marco conceptual para la gestión de las interacciones naturaleza- sociedad en un mundo cambiante. Cuid. Cuad. Interdisplinar Desarro. Sosten. 3, 229–258. Martín López, B., González, J.A., Vilardy, S., 2012. Guía Docente Ciencias de la sostenibilidad, Formación avanzada en Ciencias de la Sostenibilidad: fortaleciendo las capacidades locales para gestionar el cambio global. EditPrint Ltda. Matthews, R.B., Gilbert, N.G., Roach, A., Polhill, J.G., Gotts, N.M., 2007. Agent-based land-use models: A review of applications. Landsc. Ecol. 22, 1447–1459. https://doi.org/10.1007/s10980-007-9135-1 Mazzeo N., Zurbriggen C., Trimble M., Bianchi P., Gadino I., S.M., 2017. Sostenibilidad ambiental del Uruguay: aportes desde el pensamiento resiliente. Rev. R MAYO-SUSTE, 28–31. Moglia, M., Perez, P., Burn, S., 2010. Modelling an urban water system on the edge of chaos. Environ. Model. Softw. 25, 1528–1538. https://doi.org/10.1016/j.envsoft.2010.05.002 Müller-Hansen, F., Schlüter, M., Mäs, M., Donges, J.F., Kolb, J.J., Thonicke, K., Heitzig, J., 2017. Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches. Earth Syst. Dyn. 8, 977–1007. https://doi.org/10.5194/esd-8-977-2017 Murillo, J., Busquets, D., Dalmau, J., López, B., Muñoz, V., Rodríguez-Roda, I., 2011. Improving urban wastewater management through an auction-based management of discharges. Environ. Model. Softw. 26, 689–696. https://doi.org/10.1016/j.envsoft.2011.01.005 Nahuelhual, L., Laterra, P., Villarino, S., Mastrángelo, M., Carmona, A., Jaramillo, A., Barral, P., Burgos, N., 2015. Mapping of ecosystem services: Missing links between purposes and procedures. Ecosyst. Serv. 13, 162–172. https://doi.org/10.1016/j.ecoser.2015.03.005 Nicholson, E., Mace, G.M., Armsworth, P.R., Atkinson, G., Buckle, S., Clements, T., Ewers, R.M., Fa, J.E., Gardner, T.A., Gibbons, J., Grenyer, R., Metcalfe, R., Mourato, S., Muûls, M., Osborn, D., Reuman, D.C., Watson, C., Milner-Gulland, E.J., 2009. Priority research areas for ecosystem services in a changing world. J. Appl. Ecol. 46, 1139–1144. https://doi.org/10.1111/j.1365-2664.2009.01716.x Norling, E., Edmonds, B., Meyer, R., 2013. Informal Approaches to Developing Simulation Models. Springer, Berlin, Heidelberg, pp. 39–55. https://doi.org/10.1007/978-3-540-93813-2_4 Ostrom, E., 2009. A General Framework for Analyzing Sustainability of Social-Ecological Systems. Science (80-. ). 325, 419–422. Paredis, C., Bishop, C., Bodner, D., Xi, X., Leng Poh, K., 2013. Using system dynamics for sustainable water resources management in Singapore. Procedia Comput. Sci. 16, 157–166. https://doi.org/10.1016/j.procs.2013.01.017 Park, S., Sahleh, V., Jung, S.Y., 2015. A system dynamics computer model to assess the effects of developing an alternate water source on the water supply systems management. Procedia Eng. 119, 753–760. https://doi.org/10.1016/j.proeng.2015.08.929 Phillips, C., Allen, W., Fenemor, A., Bowden, B., Young, R., 2010. Integrated catchment management research: Lessons for interdisciplinary science from the Motueka Catchment, New Zealand. Mar. Freshw. Res. 61, 749–763. https://doi.org/10.1071/MF09099 Pickett, S.T.A., Cadenasso, M.L., Grove, J.M., Groffman, P.M., Band, L.E., Boone, C.G., Burch, W.R., Grimmond, C.S.B., Hom, J., Jenkins, J.C., Law, N.L., Nilon, C.H., Pouyat, R. V., Szlavecz, K., Warren, P.S., Wilson, M.A., 2008. Beyond Urban Legends: An Emerging Framework of Urban Ecology, as Illustrated by the Baltimore Ecosystem Study. Bioscience 58, 139–150. https://doi.org/10.1641/B580208 Pidd, M., 2004. Systems Modelling: Theory and Practice. Wiley & Sons, Inc. Pidd, M., 1999. Just modeling through: A rough guide to modeling. Interfaces (Providence). 29, 118–132. https://doi.org/10.1287/inte.29.2.118 Pierce, S.A., 2006. Groundwater decision support: linking causal narratives, numerical models, and combinatorial search techniques to determine available yield for an aquifer system. Pope, A.J., Gimblett, R., 2015. Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions. Front. Environ. Sci. 3, 55. https://doi.org/10.3389/fenvs.2015.00055 Ravera, F., Hubacek, K., Reed, M., Tarrasón, D., 2011. Learning from Experiences in Adaptive Action Research: a Critical Comparison of two Case Studies Applying Participatory Scenario Development and Modelling Approaches. Environ. Policy Gov. 21, 433–453. https://doi.org/10.1002/eet.585 Renard, D., Rhemtulla, J.M., Bennett, E.M., 2015. Historical dynamics in ecosystem service bundles. Proc. Natl. Acad. Sci. 112, 13411–13416. https://doi.org/10.1073/PNAS.1502565112 Reyes, D., 2011. Descripción y Aplicaciones de los Autómatas Celulares, U.N.a.M. https://doi.org/Pii s0040-4020(02)00395-2\r10.1016/s0040-4020(02)00395-2 Reynoso Santos, R., Valdez Lazalde, J.R., Escalona Maurice, M.J., de los Santos Posadas, H.M., Pérez Hernández, M.J., 2016. Cadenas de Markov y autómatas celulares para la modelación de cambio de uso de suelo, Ingeniería hidráulica y ambiental. Centro de Investigaciones Hidráulicas, Instituto Superior Politécnico José Antonio Echeverría. https://doi.org/113195823 Rouan, M., Kerbiriou, C., Levrel, H., Etienne, M., 2010. A co-modelling process of social and natural dynamics on the isle of Ouessant: Sheep, turf and bikes. Environ. Model. Softw. 25, 1399–1412. https://doi.org/10.1016/j.envsoft.2009.10.010 Rounsevell, Mark D A, Pedroli, B., Erb, K.-H., Gramberger, M., Gravsholt Busck, A., Haberl, H., Kristensen, S., Kuemmerle, T., Lavorel, S., Lindner, M., Lotze-Campen, H., Metzger, M.J., Murray-Rust, D., Popp, A., Pérez-Soba, M., Reenberg, A., Vadineanu, A., Verburg, P.H., Wolfslehner, B., 2012. Challenges for land system science. Land use policy 29, 899–910. https://doi.org/10.1016/j.landusepol.2012.01.007 Rounsevell, M. D.A., Robinson, D.T., Murray-Rust, D., 2012. From actors to agents in socio-ecological systems models. Philos. Trans. R. Soc. B Biol. Sci. 367, 259–269. https://doi.org/10.1098/rstb.2011.0187 Ruth, M., Hannon, B., 1997. Modeling dynamic economic systems. Springer Verlag 339. Salliou, N., Barnaud, C., Vialatte, A., Monteil, C., 2017. A participatory Bayesian Belief Network approach to explore ambiguity among stakeholders about socio-ecological systems. Environ. Model. Softw. 96, 199–209. https://doi.org/10.1016/j.envsoft.2017.06.050 Schmolke, A., Thorbek, P., Deangelis, D.L., Grimm, V., 2010. Ecological models supporting environmental decision making: a strategy for the future. Trends Ecol. Evol. 25, 479–486. https://doi.org/10.1016/j.tree.2010.05.001 Scholz, R.W., Gallati, J., Le, Q.B., Seidl, R., 2011. Integrated systems modeling of complex human-environment systems, in: Environmental Literacy in Science and Society: From Knowledge to Decisions. pp. 341–372. https://doi.org/10.1017/CBO9780511921520.017 Schreinemachers, P., Berger, T., 2011. An agent-based simulation model of human-environment interactions in agricultural systems. Environ. Model. Softw. 26, 845–859. https://doi.org/10.1016/j.envsoft.2011.02.004 Serna-Chavez, H.M., Schulp, C.J.E., van Bodegom, P.M., Bouten, W., Verburg, P.H., Davidson, M.D., 2014. A quantitative framework for assessing spatial flows of ecosystem services. Ecol. Indic. 39, 24–33. https://doi.org/10.1016/j.ecolind.2013.11.024 Shao, H., 2017. Decomposing aggregate risk into marginal risks under partial information: A top-down method. Stat. Probab. Lett. 124, 97–100. https://doi.org/10.1016/j.spl.2017.01.015 Simon, C., Etienne, M., 2010. A companion modelling approach applied to forest management planning. Environ. Model. Softw. 25, 1371–1384. https://doi.org/10.1016/j.envsoft.2009.09.004 Stave, K., 2010. Participatory system dynamics modeling for sustainable environmental management: Observations from four cases. Sustainability 2, 2762–2784. https://doi.org/10.3390/su2092762 Sterman, J., 2000. Business dynamics : systems thinking and modeling for a complex world. Irwin/McGraw-Hill. Subedi, P., Subedi, K., Thapa, B., 2013. Application of a Hybrid Cellular Automaton – Markov (CA-Markov) Model in Land-Use Change Prediction: A Case Study of Saddle Creek Drainage Basin, Florida. Appl. Ecol. Environ. Sci. 1, 126–132. https://doi.org/10.12691/aees-1-6-5 Swanson, J., 2002. Business Dynamics—Systems Thinking and Modeling for a Complex World, 2nd editio. ed, Journal of the Operational Research Society. McGraw-Hill, Boston, U.S. https://doi.org/10.1057/palgrave.jors.2601336 Sweeney, L.B., Sterman, J., 2000. Bathtub Dynamics : Initial Results of a Systems Thinking Inventory Bathtub Dynamics : Initial Results of a Systems Thinking Inventory 16, 249–286. Tsai, Y., Zia, A., Koliba, C., Bucini, G., Guilbert, J., Beckage, B., 2015. An interactive land use transition agent-based model (ILUTABM): Endogenizing human-environment interactions in the Western Missisquoi Watershed. Land use policy 49, 161–176. https://doi.org/10.1016/j.landusepol.2015.07.008 Turner, B.L., Matson, P.A., McCarthy, J.J., Corell, R.W., Christensen, L., Eckley, N., Hovelsrud-Broda, G.K., Kasperson, J.X., Kasperson, R.E., Luers, A., others, 2003. Illustrating the coupled human–environment system for vulnerability analysis: three case studies. Proc. Natl. Acad. Sci. 100, 8080–8085. Urquiza Gómez, A., Cadenas, H., 2015. Sistemas socio-ecológicos: elementos teóricos conceptuales para la discusión en torno a vulnerabilidad hídrica. L’Ordinaire des Amériques 218, online. https://doi.org/10.4000/orda.1774 Haut de page Auteurs Van Voorn, G.A.K., Verburg, R.W., Kunseler, E.-M., Vader, J., Janssen, P.H.M., 2016. A checklist for model credibility, salience, and legitimacy to improve information transfer in environmental policy assessments. Environ. Model. Softw. 83, 224–236. https://doi.org/10.1016/j.envsoft.2016.06.003 Verburg, P.H., Dearing, J.A., Dyke, J.G., Van Der Leeuw, S., Seitzinger, S., Steffen, W., Syvitski, J., 2016. Methods and approaches to modelling the Anthropocene. Glob. Environ. Chang. 39, 328–340. https://doi.org/10.1016/j.gloenvcha.2015.08.007 Verhoog, R., Ghorbani, A., Dijkema, G.P.J., 2016. Modelling socio-ecological systems with MAIA: A biogas infrastructure simulation. Environ. Model. Softw. 81, 72–85. https://doi.org/10.1016/j.envsoft.2016.03.011 Voinov, A., Seppelt, R., Reis, S., Nabel, J.E.M.S., Shokravi, S., 2014. Values in socio-environmental modelling: Persuasion for action or excuse for inaction q. Environ. Model. Softw. 53, 207–212. https://doi.org/10.1016/j.envsoft.2013.12.005 Von Neumann, J., Burks, A.W., 1966. Theory of self-Reproducing Automata. University of Illinois Press, Champign-USA. Wächter, P., 2011. Thinking in systems – a primer, Environmental Politics. https://doi.org/10.1080/09644016.2011.589585 Wallentin, G., Neuwirth, C., 2017. Dynamic hybrid modelling: Switching between AB and SD designs of a predator-prey model. Ecol. Modell. 345, 165–175. https://doi.org/10.1016/j.ecolmodel.2016.11.007 Whelan, G., Kim, K., Pelton, M.A., Castleton, K.J., Laniak, G.F., Wolfe, K., Parmar, R., Babendreier, J., Galvin, M., 2014. Design of a component-based integrated environmental modeling framework. Environ. Model. Softw. 55, 1–24. https://doi.org/10.1016/j.envsoft.2014.01.016 Williamson, O.E., 2000. The new institutional economics: Taking stock, looking ahead. J. Econ. Lit. https://doi.org/10.1257/jel.38.3.595 Wu, M., Ren, X., Che, Y., Yang, K., 2015. A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China. Environ. Manage. 402–419. https://doi.org/10.1007/s00267-015-0512-2 Yang, J., Chen, F., Xi, J., Xie, P., Li, C., 2014. A Multitarget Land Use Change Simulation Model Based on Cellular Automata and Its Application. Abstr. Appl. Anal. 2014, 1–11. https://doi.org/10.1155/2014/375389 Zhang, L., Nan, Z., Yu, W., Ge, Y., 2015. Modeling land use and land cover change and hydrological responses under consisent climate change scenarios in the Heihe River Basin, China. Water Resour. Manag. 29, 4701–4717. |
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Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Villegas Palacio, Clara Inés9bab9890d6e63f22b4b9ead6f09a5085600Arango Aramburo, Santiago214c2102e45a3ac8004821f24543d086600Berrio Giraldo, Linda Ivette0cfd03d5bb8cf2c410eaab3753a9ffd36002021-06-18T14:47:59Z2021-06-18T14:47:59Z2020-07-30https://repositorio.unal.edu.co/handle/unal/79646Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, mapasEl mundo tiene la urgencia de implementar estrategias que permitan la gestión integrada y sostenible de los ecosistemas terrestres, considerando la transformación acelerada y el deterioro de los sistemas ecológicos por la acción antropogénica, además de la variabilidad de los procesos naturales y los efectos del cambio climático. Los cambios de cobertura y uso del suelo siguen siendo uno de los motores de cambio más importantes de los sistemas socio-ecológicos (SSE) en todo el mundo. Una gestión inadecuada del suelo puede socavar la prestación futura de los servicios ecosistémicos, por lo tanto, es importante un apropiado diseño de políticas de gestión del territorio. Para lograr buenas políticas se requiere un entendimiento de los SSE a través de la comprensión de los sistemas naturales y sociales y sus interacciones. El uso de modelos de simulación proporciona una metodología para una comprensión profunda de los procesos ambientales. Los modelos además la generación de alertas tempranas, el análisis de escenarios y la evaluación de políticas sobre posibles desafíos futuros. La modelación de sistemas complejos, en particular los SSE, es motivada por una amplia gama de preguntas, y así los modelos de simulación de sistemas socio-ecológicos existentes difieren en alcance, propósito y estructura. En el área de investigación de simulación de SSE existen retos que pueden ser abordados para obtener herramientas confiables que permitan comprender el funcionamiento de los mismos, analizar cómo ha sido su trayectoria, diagnosticar el estado actual y desarrollar una evaluación exante de diferentes políticas y estrategias a ser implementadas. Uno de los retos significativos reportados por la literatura es la consideración de las interacciones en doble vía entre los sistemas sociales y naturales para su modelación, conformando ciclos de realimentación. Esta tesis desarrolla un modelo en dinámica de sistemas para comprender la dinámica de transición de cobertura y uso del suelo de la cuenca de Río Grande, ubicado en los Andes colombianos, y su incidencia en la provisión de los servicios ecosistémicos de cantidad de agua superficial y control de la erosión. Este modelo incluye las interacciones humano-naturaleza de forma integrada y las relaciones en doble vía que resultan de las interacciones entre el sistema social y natural para un caso particular. Para desarrollar el modelo, se consideraron los pasos para la modelación de sistemas complejos, los enfoques de modelación que se han usado en la literatura y los criterios que son importantes en el momento de la selección del enfoque de modelación. Este modelo incluye un indicador de sostenibilidad como contribución a la evaluación de sostenibilidad de SSE. Las pruebas de verificación y validación del modelo mostraron resultados satisfactorios y robustos que apoyan la utilidad del modelo para analizar la sostenibilidad de este SSE. El modelo permite la integración de los sistemas natural, económico y socio-cultural ya que involucra variables claves de cada uno de éstos. Se hace uso del modelo para analizar el efecto que tienen diferentes políticas ante diferentes escenarios de cambio climático y del contexto. Los escenarios analizados están estrechamente relacionados con la situación actual de la región. La validación del modelo incluyó tanto su estructura como su capacidad de replicar el comportamiento histórico para el periodo comprendido entre 1986-2015, para luego analizar escenarios hacia el 2040. En este trabajo se encontró que la sostenibilidad de la cuenca es susceptible a todos los escenarios que se evaluaron, algunos generando mayor efecto que otros. De igual forma se encontró que, una combinación de política de restricciones con cualquier tipo de política que otorgue algún incentivo de conservación permite mejorar la sostenibilidad del SSE ya que se garantizan la provisión de servicios ecosistémicos (regulación hídrica y control de la erosión), pero a su vez los ingresos económicos que se generan por los incentivos influyen positivamente en las contribuciones del capital económico para la región. Además, se evalúan las diferencias en la modelación de SSE cuando se consideran y cuando no las interacciones en doble vía. Para esto, se generaron dos modelos adicionales a partir del modelo propuesto inicialmente. En uno de los modelos, el sistema social se encuentra restringido por una salida del sistema natural y, en el otro modelo, el sistema natural está sujeto a perturbaciones del sistema social. Los resultados fueron comparados de acuerdo con diferentes variables de salidas como coberturas, erosión, disponibilidad de agua y beneficios netos de actividades económicas. Se encontraron diferencias cuando se comparan los resultados de los tres modelos. Los resultados indican que las trayectorias de las variables de salida del modelo cambian de acuerdo a la conceptualización del SSE y de la consideración de mecanismos de realimentación o las interacciones en doble vía entre el subsistema social y natural. (Tomado de la fuente)The world has the urgency to implement strategies that allow the integrated and sustainable management of terrestrial ecosystems, considering the accelerated transformation and deterioration of ecological systems by human activities, together with the variability of natural processes and the effects of climate change. Land use and land cover changes remain as the most important drivers of change in socio-ecological systems (SES) worldwide. Inadequate land management can undermine the future provision of ecosystem services; therefore, an appropriate design of land management policies is important. Achieving good policy requires an understanding of socio-ecological systems by understanding both the natural and the social systems together with their interactions. The use of simulation models provides a methodology for deepening our understanding of environmental processes, early warnings, scenario analysis and ex-ante policy evaluation of possible future challenges. The modeling of complex systems, particulary SES, is motivated by a wide range of questions, thus the existing simulation models of SES differ in scope, purpose and structure. In the research line of socio-ecological systems simulation there are challenges that must be addressed to obtain reliable tools that allow understanding of the functioning of SES, analyze the trajectories of the SES, diagnose the current state and develop an ex-ante evaluation before different policies and strategies are to be implemented. One of the significant challenges reported by the literature is the consideration of two-way interactions between social and natural systems for modeling, forming feedbacks loops. This thesis develops a model in system dynamics to understand the dynamics of land use and land cover change in a socio-ecological system located in the Colombian Andes and its impact on the provision of quantity ecosystem services of surface water and erosion control. This model includes humannature interactions and the two-way relationships that result from the interactions between the social and natural system. To develop the model, we considered the steps for modelling complex systems, the modelling approaches that have been used in the literature and the criteria that are important in selecting the modelling approach. This model includes a sustainability indicator as a contribution to the evaluation of sustainability of socio-ecological systems. The verification and validation tests of the model showed satisfactory and robust results that support the usefulness of the model to analyze the sustainability of this SES. The model allows the integration of natural, economic and socio-cultural systems as it involves key variables of each of these. The model is used to analyze the effect that different policies and different climate change scenarios have on the SES. The analyzed scenarios are closely related to the current situation in the region. The model was validated for both, in its structure and its ability to replicate historical behavior for the period spanning 1986-2015, and then analyze scenarios towards 2040. It was found that, a combination of policy restrictions with any type of policy that provides some conservation incentives allows improving the sustainability of the SES since the provision of ecosystem services (water regulation and erosion control) are guaranteed, but the economic income generated by the incentives positively influences the contributions of economic capital to the region. In addition, the thesis evaluates differences between simulation outputs when considering two-way interactions and when they are not included. For this, two additional models were generated from the model proposed above. In one of the models the social system is restricted by an output from the natural system and, in the other model, the natural system is subject to disturbances of the social system. The results were compared according to different output variables such as land cover, erosion, water availability and net benefits of economic activities. Differences were found when comparing the results of the three models. The results indicate that the trajectories of the output variables of the model change according to the conceptualization of the SES and the consideration of feedback mechanisms or two-way interactions between the natural and social subsystem. (Tomado de la fuente)DoctoradoDoctora en IngenieríaServicios Ecosistémicos y Planificación de Recursos182 páginasapplication/pdfspaUniversidad Nacional de ColombiaMedellín - Minas - Doctorado en Ingeniería - Recursos HidráulicosDepartamento de Geociencias y Medo AmbienteFacultad de MinasMedellínUniversidad Nacional de Colombia - Sede Medellín620 - Ingeniería y operaciones afines::627 - Ingeniería hidráulicaEcosistemasCuencas hidrográficas - ColombiaSistemas socio-ecológicosModelación integradaEnfoques de modelaciónSostenibilidadEscenariosInteracciones en doble víaSocio-ecological systemsIntegrated modelingModeling approachesSustainabilityScenariosTwo-way interactionsDinámica de sistemas socio-ecológicos en cuencas hidrográficas de media montaña, ColombiaDynamics of socio-ecological systems in mountain basin, ColombiaTrabajo de grado - Doctoradoinfo:eu-repo/semantics/doctoralThesisinfo:eu-repo/semantics/acceptedVersionhttp://purl.org/coar/resource_type/c_db06Texthttp://purl.org/redcol/resource_type/TDColombiaAbram, J.J., Dyke, J.G., 2018. Structural Loop Analysis of Complex Ecological Systems. Ecol. Econ. 154, 333–342. https://doi.org/10.1016/j.ecolecon.2018.08.011 Ahmad, S., Prashar, D., 2010. Evaluating Municipal Water Conservation Policies Using a Dynamic Simulation Model. Water Resour Manag. 24, 3371–3395. https://doi.org/10.1007/s11269-010-9611-2 Alexander, S.M., Andrachuk, M., Armitage, D., 2016. Navigating governance networks for community-based conservation. Front. Ecol. Environ. 14, 155–164. https://doi.org/10.1002/fee.1251 An, L., 2012. Modeling human decisions in coupled human and natural systems: Review of agent-based models. Ecol. Modell. 229, 25–36. https://doi.org/10.1016/j.ecolmodel.2011.07.010 Anderies, J.M., Janssen, M. a, Ostrom, E., 2004. A Framework to Analyze the Robustness of Social-Ecological Systems from an Institutional Perspective. Ecol. Soc. 9, 1–18. https://doi.org/18 Anselme, B., Bousquet, F., Lyet, A., Etienne, M., Fady, B., Le Page, C., 2010. Modelling of spatial dynamics and biodiversity conservation on Lure mountain (France). Environ. Model. Softw. 25, 1385–1398. https://doi.org/10.1016/j.envsoft.2009.09.001 Anwar, S.M., Jeanneret, C.A., Parrott, L., Marceau, D.J., 2007. Conceptualization and implementation of a multi-agent model to simulate whale-watching tours in the St. Lawrence Estuary in Quebec, Canada. Environ. Model. Softw. 22, 1775–1787. https://doi.org/10.1016/j.envsoft.2007.02.007 Aumann, C.A., 2006. A methodology for developing simulation models of complex systems. https://doi.org/10.1016/j.ecolmodel.2006.11.005 Bagstad, K.J., Johnson, G.W., Voigt, B., Villa, F., 2013. Spatial dynamics of ecosystem service flows: A comprehensive approach to quantifying actual services. Ecosyst. Serv. 4, 117–125. https://doi.org/10.1016/j.ecoser.2012.07.012 Baños-González, I., Martínez-Fernández, J., Esteve-Selma, M.Á., 2013. Dynamic simulation of socio-ecological Systems: sustainability in Biosphere Reserves. Ecosistemas 22, 74–83. https://doi.org/10.7818/ecos.2013.22-3.11 Barlas, Y., 1996. Formal aspects of model validity and validation in system dynamics. Syst. Dyn. Rev. 12, 183–210. https://doi.org/10.1002/(SICI)1099-1727(199623)12:3<183::AID-SDR103>3.0.CO;2-4 Barnaud, C., Bousquet, F., Trebuil, G., 2008. Multi-agent simulations to explore rules for rural credit in a highland farming community of Northern Thailand. https://doi.org/10.1016/j.ecolecon.2007.10.022 BenDor, T.K., Kaza, N., 2012. A theory of spatial system archetypes. Syst. Dyn. Rev. 28, 109–130. https://doi.org/10.1002/sdr.1470 Berrouet, L., Villegas-Palacio, C., Botero, V., 2019. A social vulnerability index to changes in ecosystem services provision at local scale: A methodological approach. Environ. Sci. Policy 93, 158–171. Berrouet, L.M., 2018. Vulnerabilidad de sistemas sociales frente a la modificación de servicios ecosistémicos en cuencas hidrográficas de media montaña. Universidad Nacional de Colombia Sede Medellín. Berrouet, L.M., Machado, J., Villegas-Palacio, C., 2018. Vulnerability of socio—ecological systems: A conceptual Framework. Ecol. Indic. 84, 632–647. https://doi.org/10.1016/j.ecolind.2017.07.051 Bodin, O., Tengo, M., 2012. Disentangling intangible social-ecological systems. Glob. Environ. Chang. 22, 430–439. https://doi.org/10.1016/j.gloenvcha.2012.01.005 Bolognesi, T., Ciancia, V., 2017. Exploring nominal cellular automata. J. Log. Algebr. Methods Program. 93, 23–41. https://doi.org/10.1016/J.JLAMP.2017.08.001 Bousquet, F., Le Page, C., 2004. Multi-agent simulations and ecosystem management: A review. Ecol. Modell. 176, 313–332. https://doi.org/10.1016/j.ecolmodel.2004.01.011 Chan, K.M.A., Guerry, A.D., Balvanera, P., Klain, S., Satterfield, T., Basurto, X., Bostrom, A., Chuenpagdee, R., Gould, R., Halpern, B.S., Hannahs, N., Levine, J., Norton, B., Ruckelshaus, M., Russell, R., Tam, J., Woodside, U., 2012. Where are Cultural and Social in Ecosystem Services? A Framework for Constructive Engagement. Bioscience 62, 744–756. https://doi.org/10.1525/bio.2012.62.8.7 Change, I.P. on C., 2013. Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of hte Intergovernmental Panel on Climate Change. Chen, Y., Bakker, M.M., Ligtenberg, A., Bregt, A.K., 2016. How are feedbacks represented in land models? Land 5, 29. https://doi.org/10.3390/land5030029 Ciftcioglu, G.C., 2017. Assessment of the resilience of socio-ecological production landscapes and seascapes: A case study from Lefke Region of North Cyprus. Ecol. Indic. 73, 128–138. https://doi.org/10.1016/j.ecolind.2016.09.036 Claessens, L., Schoorl, J.M., Verburg, P.H., Geraedts, L., Veldkamp, A., 2009. Modelling interactions and feedback mechanisms between land use change and landscape processes. Agric. Ecosyst. Environ. 129, 157–170. https://doi.org/10.1016/j.agee.2008.08.008 Collins, Scott L, Carpenter, S.R., Swinton, S.M., Orenstein, D.E., Childers, D.L., Gragson, T.L., Grimm, N.B., Grove, J.M., Harlan, S.L., Kaye, J.P., Knapp, A.K., Kofinas, G.P., Magnuson, J.J., McDowell, W.H., Melack, J.M., Ogden, L.A., Robertson, G.P., Smith, M.D., Whitmer, A.C., 2011. An integrated conceptual framework for long-term social–ecological research. Front. Ecol. Environ. 9, 351–357. https://doi.org/10.1890/100068 Colomer, M.À., Montori, A., García, E., Fondevilla, C., 2014. Using a bioinspired model to determine the extinction risk of Calotriton asper populations as a result of an increase in extreme rainfall in a scenario of climatic change. Ecol. Modell. 281, 1–14. https://doi.org/10.1016/j.ecolmodel.2014.02.018 Cooper, G.S., Dearing, J.A., 2019. Modelling future safe and just operating spaces in regional social-ecological systems. Sci. Total Environ. 651, 2105–2117. https://doi.org/10.1016/j.scitotenv.2018.10.118 Coyle, R.G., 1996. System dynamics modelling : a practical approach. Chapman & Hall. David, N., 2013. Validating Simulations. Springer, Berlin, Heidelberg, pp. 135–171. https://doi.org/10.1007/978-3-540-93813-2_8 Davis, J.P., Eisenhardt, K.M., Bingham, C.B., 2007. Developing theory through simulation methods. Acad. Manag. Rev 32, 480–499. Díaz, S., Demissew, S., Carabias, J., Joly, C., Lonsdale, M., Ash, N., Larigauderie, A., Adhikari, J.R., Arico, S., Báldi, A., Bartuska, A., Baste, I.A., Bilgin, A., Brondizio, E., Chan, K.M.A., Figueroa, V.E., Duraiappah, A., Fischer, M., Hill, R., Koetz, T., Leadley, P., Lyver, P., Mace, G.M., Martin-Lopez, B., Okumura, M., Pacheco, D., Pascual, U., Pérez, E.S., Reyers, B., Roth, E., Saito, O., Scholes, R.J., Sharma, N., Tallis, H., Thaman, R., Watson, R., Yahara, T., Hamid, Z.A., Akosim, C., Al-Hafedh, Y., Allahverdiyev, R., Amankwah, E., Asah, T.S., Asfaw, Z., Bartus, G., Brooks, A.L., Caillaux, J., Dalle, G., Darnaedi, D., Driver, A., Erpul, G., Escobar-Eyzaguirre, P., Failler, P., Fouda, A.M.M., Fu, B., Gundimeda, H., Hashimoto, S., Homer, F., Lavorel, S., Lichtenstein, G., Mala, W.A., Mandivenyi, W., Matczak, P., Mbizvo, C., Mehrdadi, M., Metzger, J.P., Mikissa, J.B., Moller, H., Mooney, H.A., Mumby, P., Nagendra, H., Nesshover, C., Oteng-Yeboah, A.A., Pataki, G., Roué, M., Rubis, J., Schultz, M., Smith, P., Sumaila, R., Takeuchi, K., Thomas, S., Verma, M., Yeo-Chang, Y., Zlatanova, D., 2015. The IPBES Conceptual Framework - connecting nature and people. Curr. Opin. Environ. Sustain. 14, 1–16. https://doi.org/10.1016/j.cosust.2014.11.002 Duespohl, M., Frank, S., Doell, P., 2012. A Review of Bayesian Networks as a Participatory Modeling Approach in Support of Sustainable Environmental Management. J. Sustain. Dev. 5, 0–18. https://doi.org/10.5539/jsd.v5n12p1 Duncan, C., Thompson, J.R., Pettorelli, N., 2015. The quest for a mechanistic understanding of biodiversity–ecosystem services relationships. Proc. R. Soc. B Biol. Sci. 282, 20151348. https://doi.org/10.1098/rspb.2015.1348 Elmahdi, A.., McFarlane, D.., 2010. DSS and MAF (multi-agencies framework) for sustainable water management, Modelling for Environment’s Sake: Proceedings of the 5th Biennial Conference of the International Environmental Modelling and Software Society, iEMSs 2010. Ottawa. Elsawah, S., Mclucas, A., Mazanov, J., 2015. Communicating About Water Issues in Australia: A Simulation/Gaming Approach. Simul. Gaming 46, 713–741. https://doi.org/10.1177/1046878115580410 Elsawah, S., Pierce, S.A., Hamilton, S.H., van Delden, H., Haase, D., Elmahdi, A., Jakeman, A.J., 2017. An overview of the system dynamics process for integrated modelling of socio-ecological systems: Lessons on good modelling practice from five case studies. Environ. Model. Softw. 93, 127–145. https://doi.org/10.1016/j.envsoft.2017.03.001 Filatova, T., Verburg, P.H., Parker, D.C., Stannard, C.A., 2013. Spatial agent-based models for socio-ecological systems: Challenges and prospects. Environ. Model. Softw. 45, 1–7. https://doi.org/10.1016/j.envsoft.2013.03.017 Fondevilla, C., Àngels Colomer, M., Fillat, F., Tappeiner, U., 2016. Using a new PDP modelling approach for land-use and land-cover change predictions: A case study in the Stubai Valley (Central Alps). Ecol. Modell. 322, 101–114. https://doi.org/10.1016/j.ecolmodel.2015.11.016 Forrester, J., 2009. Some basic concepts in system dynamics. Sloan Sch. Manag. … 1–17. Forrester, J.W., 1971. Counterintuitive behaviour of social systems. Theory Decis. 2, 109–140. Gaines, S.D., Dee, L.E., Allesina, S., Bonn, A., Eklöf, A., Gaines, S.D., Hines, J., Jacob, U., Mcdonald-madden, E., Possingham, H., 2017. Operationalizing Network Theory for Ecosystem Service Assessments Operationalizing Network Theory for Ecosystem Service Assessments. Trends Ecol. Evol. 32, 118–130. https://doi.org/10.1016/j.tree.2016.10.011 Gotts, N.M., van Voorn, G.A.K., Polhill, J.G., Jong, E. de, Edmonds, B., Hofstede, G.J., Meyer, R., 2018. Agent-based modelling of socio-ecological systems: Models, projects and ontologies. Ecol. Complex. https://doi.org/10.1016/j.ecocom.2018.07.007 Halmy, M.W.A., Gessler, P.E., Hicke, J.A., Salem, B.B., 2015. Land use/land cover change detection and prediction in the north-western coastal desert of Egypt using Markov-CA. Appl. Geogr. 63, 101–112. https://doi.org/10.1016/j.apgeog.2015.06.015 Hamilton, S.H., Elsawah, S., Guillaume, J.H.A., Jakeman, A.J., Pierce, S.A., 2015. Integrated assessment and modelling: Overview and synthesis of salient dimensions. https://doi.org/10.1016/j.envsoft.2014.12.005 Hare, M., Deadman, P., 2004. Further towards a taxonomy of agent-based simulation models in environmental management. Math. Comput. Simul. 64, 25–40. https://doi.org/10.1016/S0378-4754(03)00118-6 Hoshino, E., van Putten, I., Girsang, W., Resosudarmo, B.P., Yamazaki, S., 2016. A Bayesian belief network model for community-based coastal resource management in the Kei Islands, Indonesia. Ecol. Soc. 21, art16. https://doi.org/10.5751/ES-08285-210216 Howick, S., Eden, C., Ackermann, F., Williams, T., 2007. Building confidence in models for multiple audiences: The modelling cascade. https://doi.org/10.1016/j.ejor.2007.02.027 Ilachinski, A., 2001. Cellular Automata. A discrete Universe. WORLD SCIENTIFIC. https://doi.org/10.1142/4702 Jakeman, A.J., Letcher, R.A., Norton, J.P., Au, A.J., Jakeman, ), 2006. Ten iterative steps in development and evaluation of environmental models. Environ. Model. Softw. 21, 602–614. https://doi.org/10.1016/j.envsoft.2006.01.004 Kelly, R.A.. B., Jakeman, A.J.., Barreteau, O.., Borsuk, M.E.., ElSawah, S.., Hamilton, S.H.., Henriksen, H.J.., Kuikka, S.., Maier, H.R.., Rizzoli, A.E.., van Delden, H.. I., Voinov, A.A.., 2013. Selecting among five common modelling approaches for integrated environmental assessment and management. Environ. Model. Softw. 47, 159–181. https://doi.org/10.1016/j.envsoft.2013.05.005 Kim, B.S., Kim, T.G., 2019. Cooperation of simulation and data model for performance analysis of complex systems. Int. J. Simul. Model. 18, 608–619. https://doi.org/10.2507/IJSIMM18(4)491 Kok, K., 2009. The potential of Fuzzy Cognitive Maps for semi-quantitative scenario development, with an example from Brazil. Glob. Environ. Chang. 19, 122–133. https://doi.org/10.1016/j.gloenvcha.2008.08.003 Korb, K.B., Nicholson, A.E., 2011. Bayesian artificial intelligence. CRC Press. Kramer, D.B., Hartter, J., Boag, A.E., Jain, M., Stevens, K., Nicholas, K.A., McConnell, W.J., Liu, J., 2017. Top 40 questions in coupled human and natural systems (CHANS) research. Ecol. Soc. 22, art44. https://doi.org/10.5751/ES-09429-220244 Lambin, E.F., Meyfroidt, P., 2010. Land use transitions: Socio-ecological feedback versus socio-economic change. Land use policy 27, 108–118. https://doi.org/10.1016/j.landusepol.2009.09.003 Lauf, S., Haase, D., Hostert, P., Lakes, T., Kleinschmit, B., 2012. Uncovering land-use dynamics driven by human decision-making - A combined model approach using cellular automata and system dynamics. Environ. Model. Softw. 27–28, 71–82. https://doi.org/10.1016/j.envsoft.2011.09.005 Levontin, P., Kulmala, S., Haapasaari, P., Kuikka, S., 2011. Integration of biological, economic, and sociological knowledge by Bayesian belief networks: the interdisciplinary evaluation of potential management plans for Baltic salmon. ICES J. Mar. Sci. 68, 632–638. https://doi.org/10.1093/icesjms/fsr004 Liu, J., Dietz, T., Carpenter, S.R., Alberti, M., Folke, C., Moran, E., Pell, A.N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C.L., Schneider, S.H., Taylor, W.W., 2007. Complexity of Coupled Human and Natural Systems. Science (80-. ). 317, 1513–1516. https://doi.org/10.1126/science.1144004 Liu, Y., Gupta, H., Springer, E., Wagener, T., 2008. Linking science with environmental decision making: Experiences from an integrated modeling approach to supporting sustainable water resources management. https://doi.org/10.1016/j.envsoft.2007.10.007 Liu, Y., Long, H., 2016. Land use transitions and their dynamic mechanism: The case of the Huang-Huai-Hai Plain. J. Geogr. Sci. 26, 515–530. https://doi.org/10.1007/s11442-016-1283-2 López-Carr, D., Davis, J., Jankowska, M.M., Grant, L., López-Carr, A.C., Clark, M., 2012. Space versus place in complex human–natural systems: Spatial and multi-level models of tropical land use and cover change (LUCC) in Guatemala. Ecol. Modell. 229, 64–75. https://doi.org/10.1016/j.ecolmodel.2011.08.020 Luna-Reyes, L.F., Andersen, D.L., 2003. Collecting and analyzing qualitative data for system dynamics: Methods and models. Syst. Dyn. Rev. 19, 271–296. https://doi.org/10.1002/sdr.280 Martín-López, B., García-Llorente, M., Palomo, I., Montes, C., García-Nieto, A.P., Quintas-Soriano, C., 2014. Collaborative mapping of ecosystem services: The role of stakeholders׳ profiles. Ecosyst. Serv. 13, 141–152. https://doi.org/10.1016/j.ecoser.2014.11.006 Martín-López, B., Gómez-Baggethun, E., Montes, C., 2009. Un marco conceptual para la gestión de las interacciones naturaleza- sociedad en un mundo cambiante. Cuid. Cuad. Interdisplinar Desarro. Sosten. 3, 229–258. Martín López, B., González, J.A., Vilardy, S., 2012. Guía Docente Ciencias de la sostenibilidad, Formación avanzada en Ciencias de la Sostenibilidad: fortaleciendo las capacidades locales para gestionar el cambio global. EditPrint Ltda. Matthews, R.B., Gilbert, N.G., Roach, A., Polhill, J.G., Gotts, N.M., 2007. Agent-based land-use models: A review of applications. Landsc. Ecol. 22, 1447–1459. https://doi.org/10.1007/s10980-007-9135-1 Mazzeo N., Zurbriggen C., Trimble M., Bianchi P., Gadino I., S.M., 2017. Sostenibilidad ambiental del Uruguay: aportes desde el pensamiento resiliente. Rev. R MAYO-SUSTE, 28–31. Moglia, M., Perez, P., Burn, S., 2010. Modelling an urban water system on the edge of chaos. Environ. Model. Softw. 25, 1528–1538. https://doi.org/10.1016/j.envsoft.2010.05.002 Müller-Hansen, F., Schlüter, M., Mäs, M., Donges, J.F., Kolb, J.J., Thonicke, K., Heitzig, J., 2017. Towards representing human behavior and decision making in Earth system models – an overview of techniques and approaches. Earth Syst. Dyn. 8, 977–1007. https://doi.org/10.5194/esd-8-977-2017 Murillo, J., Busquets, D., Dalmau, J., López, B., Muñoz, V., Rodríguez-Roda, I., 2011. Improving urban wastewater management through an auction-based management of discharges. Environ. Model. Softw. 26, 689–696. https://doi.org/10.1016/j.envsoft.2011.01.005 Nahuelhual, L., Laterra, P., Villarino, S., Mastrángelo, M., Carmona, A., Jaramillo, A., Barral, P., Burgos, N., 2015. Mapping of ecosystem services: Missing links between purposes and procedures. Ecosyst. Serv. 13, 162–172. https://doi.org/10.1016/j.ecoser.2015.03.005 Nicholson, E., Mace, G.M., Armsworth, P.R., Atkinson, G., Buckle, S., Clements, T., Ewers, R.M., Fa, J.E., Gardner, T.A., Gibbons, J., Grenyer, R., Metcalfe, R., Mourato, S., Muûls, M., Osborn, D., Reuman, D.C., Watson, C., Milner-Gulland, E.J., 2009. Priority research areas for ecosystem services in a changing world. J. Appl. Ecol. 46, 1139–1144. https://doi.org/10.1111/j.1365-2664.2009.01716.x Norling, E., Edmonds, B., Meyer, R., 2013. Informal Approaches to Developing Simulation Models. Springer, Berlin, Heidelberg, pp. 39–55. https://doi.org/10.1007/978-3-540-93813-2_4 Ostrom, E., 2009. A General Framework for Analyzing Sustainability of Social-Ecological Systems. Science (80-. ). 325, 419–422. Paredis, C., Bishop, C., Bodner, D., Xi, X., Leng Poh, K., 2013. Using system dynamics for sustainable water resources management in Singapore. Procedia Comput. Sci. 16, 157–166. https://doi.org/10.1016/j.procs.2013.01.017 Park, S., Sahleh, V., Jung, S.Y., 2015. A system dynamics computer model to assess the effects of developing an alternate water source on the water supply systems management. Procedia Eng. 119, 753–760. https://doi.org/10.1016/j.proeng.2015.08.929 Phillips, C., Allen, W., Fenemor, A., Bowden, B., Young, R., 2010. Integrated catchment management research: Lessons for interdisciplinary science from the Motueka Catchment, New Zealand. Mar. Freshw. Res. 61, 749–763. https://doi.org/10.1071/MF09099 Pickett, S.T.A., Cadenasso, M.L., Grove, J.M., Groffman, P.M., Band, L.E., Boone, C.G., Burch, W.R., Grimmond, C.S.B., Hom, J., Jenkins, J.C., Law, N.L., Nilon, C.H., Pouyat, R. V., Szlavecz, K., Warren, P.S., Wilson, M.A., 2008. Beyond Urban Legends: An Emerging Framework of Urban Ecology, as Illustrated by the Baltimore Ecosystem Study. Bioscience 58, 139–150. https://doi.org/10.1641/B580208 Pidd, M., 2004. Systems Modelling: Theory and Practice. Wiley & Sons, Inc. Pidd, M., 1999. Just modeling through: A rough guide to modeling. Interfaces (Providence). 29, 118–132. https://doi.org/10.1287/inte.29.2.118 Pierce, S.A., 2006. Groundwater decision support: linking causal narratives, numerical models, and combinatorial search techniques to determine available yield for an aquifer system. Pope, A.J., Gimblett, R., 2015. Linking Bayesian and agent-based models to simulate complex social-ecological systems in semi-arid regions. Front. Environ. Sci. 3, 55. https://doi.org/10.3389/fenvs.2015.00055 Ravera, F., Hubacek, K., Reed, M., Tarrasón, D., 2011. Learning from Experiences in Adaptive Action Research: a Critical Comparison of two Case Studies Applying Participatory Scenario Development and Modelling Approaches. Environ. Policy Gov. 21, 433–453. https://doi.org/10.1002/eet.585 Renard, D., Rhemtulla, J.M., Bennett, E.M., 2015. Historical dynamics in ecosystem service bundles. Proc. Natl. Acad. Sci. 112, 13411–13416. https://doi.org/10.1073/PNAS.1502565112 Reyes, D., 2011. Descripción y Aplicaciones de los Autómatas Celulares, U.N.a.M. https://doi.org/Pii s0040-4020(02)00395-2\r10.1016/s0040-4020(02)00395-2 Reynoso Santos, R., Valdez Lazalde, J.R., Escalona Maurice, M.J., de los Santos Posadas, H.M., Pérez Hernández, M.J., 2016. Cadenas de Markov y autómatas celulares para la modelación de cambio de uso de suelo, Ingeniería hidráulica y ambiental. Centro de Investigaciones Hidráulicas, Instituto Superior Politécnico José Antonio Echeverría. https://doi.org/113195823 Rouan, M., Kerbiriou, C., Levrel, H., Etienne, M., 2010. A co-modelling process of social and natural dynamics on the isle of Ouessant: Sheep, turf and bikes. Environ. Model. Softw. 25, 1399–1412. https://doi.org/10.1016/j.envsoft.2009.10.010 Rounsevell, Mark D A, Pedroli, B., Erb, K.-H., Gramberger, M., Gravsholt Busck, A., Haberl, H., Kristensen, S., Kuemmerle, T., Lavorel, S., Lindner, M., Lotze-Campen, H., Metzger, M.J., Murray-Rust, D., Popp, A., Pérez-Soba, M., Reenberg, A., Vadineanu, A., Verburg, P.H., Wolfslehner, B., 2012. Challenges for land system science. Land use policy 29, 899–910. https://doi.org/10.1016/j.landusepol.2012.01.007 Rounsevell, M. D.A., Robinson, D.T., Murray-Rust, D., 2012. From actors to agents in socio-ecological systems models. Philos. Trans. R. Soc. B Biol. Sci. 367, 259–269. https://doi.org/10.1098/rstb.2011.0187 Ruth, M., Hannon, B., 1997. Modeling dynamic economic systems. Springer Verlag 339. Salliou, N., Barnaud, C., Vialatte, A., Monteil, C., 2017. A participatory Bayesian Belief Network approach to explore ambiguity among stakeholders about socio-ecological systems. Environ. Model. Softw. 96, 199–209. https://doi.org/10.1016/j.envsoft.2017.06.050 Schmolke, A., Thorbek, P., Deangelis, D.L., Grimm, V., 2010. Ecological models supporting environmental decision making: a strategy for the future. Trends Ecol. Evol. 25, 479–486. https://doi.org/10.1016/j.tree.2010.05.001 Scholz, R.W., Gallati, J., Le, Q.B., Seidl, R., 2011. Integrated systems modeling of complex human-environment systems, in: Environmental Literacy in Science and Society: From Knowledge to Decisions. pp. 341–372. https://doi.org/10.1017/CBO9780511921520.017 Schreinemachers, P., Berger, T., 2011. An agent-based simulation model of human-environment interactions in agricultural systems. Environ. Model. Softw. 26, 845–859. https://doi.org/10.1016/j.envsoft.2011.02.004 Serna-Chavez, H.M., Schulp, C.J.E., van Bodegom, P.M., Bouten, W., Verburg, P.H., Davidson, M.D., 2014. A quantitative framework for assessing spatial flows of ecosystem services. Ecol. Indic. 39, 24–33. https://doi.org/10.1016/j.ecolind.2013.11.024 Shao, H., 2017. Decomposing aggregate risk into marginal risks under partial information: A top-down method. Stat. Probab. Lett. 124, 97–100. https://doi.org/10.1016/j.spl.2017.01.015 Simon, C., Etienne, M., 2010. A companion modelling approach applied to forest management planning. Environ. Model. Softw. 25, 1371–1384. https://doi.org/10.1016/j.envsoft.2009.09.004 Stave, K., 2010. Participatory system dynamics modeling for sustainable environmental management: Observations from four cases. Sustainability 2, 2762–2784. https://doi.org/10.3390/su2092762 Sterman, J., 2000. Business dynamics : systems thinking and modeling for a complex world. Irwin/McGraw-Hill. Subedi, P., Subedi, K., Thapa, B., 2013. Application of a Hybrid Cellular Automaton – Markov (CA-Markov) Model in Land-Use Change Prediction: A Case Study of Saddle Creek Drainage Basin, Florida. Appl. Ecol. Environ. Sci. 1, 126–132. https://doi.org/10.12691/aees-1-6-5 Swanson, J., 2002. Business Dynamics—Systems Thinking and Modeling for a Complex World, 2nd editio. ed, Journal of the Operational Research Society. McGraw-Hill, Boston, U.S. https://doi.org/10.1057/palgrave.jors.2601336 Sweeney, L.B., Sterman, J., 2000. Bathtub Dynamics : Initial Results of a Systems Thinking Inventory Bathtub Dynamics : Initial Results of a Systems Thinking Inventory 16, 249–286. Tsai, Y., Zia, A., Koliba, C., Bucini, G., Guilbert, J., Beckage, B., 2015. An interactive land use transition agent-based model (ILUTABM): Endogenizing human-environment interactions in the Western Missisquoi Watershed. Land use policy 49, 161–176. https://doi.org/10.1016/j.landusepol.2015.07.008 Turner, B.L., Matson, P.A., McCarthy, J.J., Corell, R.W., Christensen, L., Eckley, N., Hovelsrud-Broda, G.K., Kasperson, J.X., Kasperson, R.E., Luers, A., others, 2003. Illustrating the coupled human–environment system for vulnerability analysis: three case studies. Proc. Natl. Acad. Sci. 100, 8080–8085. Urquiza Gómez, A., Cadenas, H., 2015. Sistemas socio-ecológicos: elementos teóricos conceptuales para la discusión en torno a vulnerabilidad hídrica. L’Ordinaire des Amériques 218, online. https://doi.org/10.4000/orda.1774 Haut de page Auteurs Van Voorn, G.A.K., Verburg, R.W., Kunseler, E.-M., Vader, J., Janssen, P.H.M., 2016. A checklist for model credibility, salience, and legitimacy to improve information transfer in environmental policy assessments. Environ. Model. Softw. 83, 224–236. https://doi.org/10.1016/j.envsoft.2016.06.003 Verburg, P.H., Dearing, J.A., Dyke, J.G., Van Der Leeuw, S., Seitzinger, S., Steffen, W., Syvitski, J., 2016. Methods and approaches to modelling the Anthropocene. Glob. Environ. Chang. 39, 328–340. https://doi.org/10.1016/j.gloenvcha.2015.08.007 Verhoog, R., Ghorbani, A., Dijkema, G.P.J., 2016. Modelling socio-ecological systems with MAIA: A biogas infrastructure simulation. Environ. Model. Softw. 81, 72–85. https://doi.org/10.1016/j.envsoft.2016.03.011 Voinov, A., Seppelt, R., Reis, S., Nabel, J.E.M.S., Shokravi, S., 2014. Values in socio-environmental modelling: Persuasion for action or excuse for inaction q. Environ. Model. Softw. 53, 207–212. https://doi.org/10.1016/j.envsoft.2013.12.005 Von Neumann, J., Burks, A.W., 1966. Theory of self-Reproducing Automata. University of Illinois Press, Champign-USA. Wächter, P., 2011. Thinking in systems – a primer, Environmental Politics. https://doi.org/10.1080/09644016.2011.589585 Wallentin, G., Neuwirth, C., 2017. Dynamic hybrid modelling: Switching between AB and SD designs of a predator-prey model. Ecol. Modell. 345, 165–175. https://doi.org/10.1016/j.ecolmodel.2016.11.007 Whelan, G., Kim, K., Pelton, M.A., Castleton, K.J., Laniak, G.F., Wolfe, K., Parmar, R., Babendreier, J., Galvin, M., 2014. Design of a component-based integrated environmental modeling framework. Environ. Model. Softw. 55, 1–24. https://doi.org/10.1016/j.envsoft.2014.01.016 Williamson, O.E., 2000. The new institutional economics: Taking stock, looking ahead. J. Econ. Lit. https://doi.org/10.1257/jel.38.3.595 Wu, M., Ren, X., Che, Y., Yang, K., 2015. A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China. Environ. Manage. 402–419. https://doi.org/10.1007/s00267-015-0512-2 Yang, J., Chen, F., Xi, J., Xie, P., Li, C., 2014. A Multitarget Land Use Change Simulation Model Based on Cellular Automata and Its Application. Abstr. Appl. Anal. 2014, 1–11. https://doi.org/10.1155/2014/375389 Zhang, L., Nan, Z., Yu, W., Ge, Y., 2015. Modeling land use and land cover change and hydrological responses under consisent climate change scenarios in the Heihe River Basin, China. Water Resour. 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