Publications related to Ecosystem Functional Types (EFTs) research:

  • Alcaraz-Segura et al. (2006). Identification of current ecosystem functional types in the Iberian Peninsula. Global Ecology and Biogeography 15: 200-212.
  • Alcaraz-Segura et al. (2009). Baseline characterization of major Iberian vegetation types based on the NDVI dynamics. Plant Ecology 202: 13-29.
  • Alcaraz-Segura et al. (2013). Environmental and Human Controls of Ecosystem Functional Diversity in Temperate South America. Remote Sensing 5: 127-154.
  • Cabello et al. (2008). Funcionamiento ecosistémico y evaluación de prioridades geográficas en conservación. Ecosistemas 17(3): 53-63.
  • Cabello et al. (2013). Ecosystem services assessment of national park networks for functional diversity and carbon conservation strategies using remote sensing. In Di Bella, Alcaraz-Segura Eds. Earth Observation of Ecosystem Services: 179-200.
  • Fernández et al. (2010). Ecosystem functioning of protected and altered Mediterranean environments: A remote sensing classification in Doñana, Spain. Remote Sensing of Environment 114: 211-220.
  • Huete (1999). MODIS vegetation index (MOD13). Algorithm theoretical basis document ATBD13.
  • Ivits et al. (2013). Global Biogeographical Pattern of Ecosystem Functional Types Derived From Earth Observation Datal. Remote Sensing 5(7): 3305-3330.
  • Lee et al. (2013). Effect of implementing ecosystem functional type data in a mesoscale climate model. Advances in Atmospheric Sciences 30(5): 1373-1386.
  • Lee et al. (2013). The Impact of Ecosystem Functional Type Changes on the La Plata Basin Climate. Advances in Atmospheric Sciences 30(5): 1387-1405.
  • Paruelo et al. (2001). Current distribution of ecosystem functional types in temperate South America. Ecosystems 4: 683-698.
  • Paruelo et al. (2011). El seguimiento del nivel de provisión de los servicios ecosistémicos. Valoración de Servicios Ecosistémicos. Conceptos, herramientas y aplicaciones para el ordenamiento territorial. Buenos Aires, Argentina: Ediciones INTA. p. 141-162.
  • Pérez-Hoyos et al. (2015). Identification of Ecosystem Functional Types from Coarse Resolution Imagery Using a Self-Organizing Map Approach: A Case Study for Spain. Remote Sensing 6(11): 11391-11419.
  • Pettorelli et al. (2005). Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution 20: 503-510.
  • Reynolds & Wu (1999). Do landscape structural and functional units exist? Integrating hydrology, ecosystem dynamics and biogeochemistry in complex landscapes. John Wiley & Sons, Berlin.: (ed. by J.D. Tenhunen and P. Kabat). p. 273–296.
  • Scholes et al. (1997). Plant functional types in African savannas and grasslands. Plant functional types: their relevance to ecosystem properties and global change (ed. by T.M. Smith, H.H. Shugart and F.I. Woodward). Cambridge University Press: 255-268.
  • Shugart H.H. (1997). Plant and ecosystem functional types. Plant functional types: their relevance to ecosystem properties and global change (ed. by T.M. Smith, H.H. Shugart and F.I. Woodward). Cambridge University Press: 20-45.
  • Soriano & Paruelo (1992). Biozones: vegetation units defined by functional characters identifiable with the aid of satellite sensor images. Global Ecology and Biogeography Letters: 82-89.
  • Valentini et al. (1999). Ecological controls on land–surface atmospheric interactions. Integrating hydrology, ecosystem dynamics and biogeochemistry in complex landscapes. John Wiley & Sons, Berlin.: (ed. by J.D. Tenhunen and P. Kabat). p. 105-116.
  • Volante et al. (2012). Ecosystem functional changes associated with land clearing in NW Argentina. Agriculture, ecosystems & environment 154: 12-22.
  • Walker B.H. (1997). Functional types in non-equilibrium ecosystems. Plant functional types: their relevance to ecosystem properties and global change (ed. by T.M. Smith, H.H. Shugart and F.I. Woodward). Cambridge University Press: 91-103.
  • Wang & Huang (2015). Identification and analysis of ecosystem functional types in the west of Songnen Plain. Journal of Applied Remote Sensing 9(1): 096096-096096.

Publications related to Social-Ecological Systems (SESs) research:

  • Alessa et al. (2008). Social–ecological hotspots mapping: A spatial approach for identifying coupled social–ecological space. Landscape and Urban Planning 85: 27-39.
  • Arneth et al. (2014). Global models of human decision-making for land-based mitigation and adaptation assessment. Nature Climate Change 4: 550-557.
  • Baldi et al. (2013). The imprint of humans on landscape patterns and vegetation functioning in the dry subtropics. Global Change Biology 19: 441-458.
  • Bonet-García et al. (2015). Protected areas as elicitors of human well-being in a developed region: A new synthetic (socioeconomic) approach. Biological Conservation 187: 221-229.
  • Cumming et al. (2014). Implications of agricultural transitions and urbanization for ecosystem services. Nature 515: 50-57.
  • Ellis & Ramankutty (2008). Putting people in the map: anthropogenic biomes of the world. Frontiers in Ecology and Environment 6(8): 439–447.
  • Erb (2012). How a socio-ecological metabolism approach can help to advance our understanding of changes in land-use intensity. Ecological Economics 76: 8-14.
  • Fischer-Kowalski et al. (2014) A sociometabolic reading of the Anthropocene: Modes of subsistence, population size and human impact on Earth. The Anthropocene Review 1(1): 8-33.
  • Folke et al. (2011). Reconnecting to the Biosphere. AMBIO 40: 719–738.
  • García-Llorente et al. (2015). Biophysical and sociocultural factors underlying spatial trade-offs of ecosystem services in semiarid watersheds. Ecology & Society 20(3): 39.
  • Hamann et al. (2015). Mapping social–ecological systems: Identifying ‘green-loop’ and ‘red-loop’ dynamics based on characteristic bundles of ecosystem service use. Global Environmental Change 34: 218-226.
  • Haines-Young & Potschin (2013). Common International Classification of Ecosystem Services (CICES): Consultation on Version 4, August-December 2012.
  • Jemmali & Sullivan (2014). Multidimensional Analysis of Water Poverty in MENA Region: An Empirical Comparison with Physical Indicators. Social Indicators Research 115: 253–277.
  • Krausmann et al. (2009). What determines geographical patterns of the global human appropriation of net primary production? Journal of Land Use Science 4: 15–33.
  • Liu et al. (2007). Complexity of Coupled Human and Natural Systems. Science 317: 1513-1516.
  • Liu et al. (2013). Framing Sustainability in a Telecoupled World. Ecology & Society 18(2): 26.
  • Martín-López et al. (2009). Un marco conceptual para la gestión de las interacciones naturaleza sociedad en un mundo cambiante. CUIDES, 09-3.
  • MEA (Millennium Ecosystem Assessment). (2005). Ecosystems and Human Well-being: Synthesis. Island Press, Washington, DC.
  • Queiroz et al. (2015). Mapping bundles of ecosystem services reveals distinct types of multifunctionality within a Swedish landscape. AMBIO 44(1): S89–S101.
  • Raudsepp-Hearne et al. (2010). Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. PNAS 107 (11): 5242-5247.
  • Renard et al. (2015). Historical dynamics in ecosystem service bundles. PNAS 112(43): 13411-13416.
  • Resilience Alliance. (2007). Assessing and managing resilience in social-ecological systems: Volume 2.
  • Rodríguez-Loinaz et al. (2015). Multiple ecosystem services landscape index: A tool for multifunctional landscapes conservation. Journal of Environmental Management 147: 152-163.
  • Shackleton et al. (2016). Unpacking Pandora’s Box: Understanding and Categorising Ecosystem Disservices for Environmental Management and Human Wellbeing. Ecosystems 19: 587–600.
  • Sullivan (2002). Calculating a Water Poverty Index. World Development 30(7): 1195–1210.
  • Sullivan & Meigh (2007). Integration of the biophysical and social sciences using an indicator approach: Addressing water problems at different scales. Water Resources Management 21: 111–128.
  • Vitousek (1997). Human domination of earth’s ecosystems. Science 277: 494–499.
  • Watmough et al. (2013). Predicting socioeconomic conditions from satellite sensor data in rural developing countries: A case study using female literacy in Assam, India. Applied Geography 44: 192-200.