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Hughes SJ, Cabral JA, Bastos R, et al. A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive. Sci Total Environ. 2016;565:427-439doi: 10.1016/j.scitotenv.2016.04.153.
Hughes, S. J., Cabral, J. A., Bastos, R., Cortes, R., Vicente, J., Eitelberg, D., Yu, H., Honrado, J., & Santos, M. (2016). A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive. The Science of the total environment, 565427-439. https://doi.org/10.1016/j.scitotenv.2016.04.153
Hughes, Samantha Jane, et al. "A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive." The Science of the total environment vol. 565 (2016): 427-439. doi: https://doi.org/10.1016/j.scitotenv.2016.04.153
Hughes SJ, Cabral JA, Bastos R, Cortes R, Vicente J, Eitelberg D, Yu H, Honrado J, Santos M. A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive. Sci Total Environ. 2016 Sep 15;565:427-439. doi: 10.1016/j.scitotenv.2016.04.153. Epub 2016 May 12. PMID: 27179681.
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Sci Total Environ. 2016 Sep 15;565:427-439. doi: 10.1016/j.scitotenv.2016.04.153. Epub 2016 May 12.

A stochastic dynamic model to assess land use change scenarios on the ecological status of fluvial water bodies under the Water Framework Directive.

The Science of the total environment

Samantha Jane Hughes, João Alexandre Cabral, Rita Bastos, Rui Cortes, Joana Vicente, David Eitelberg, Huirong Yu, João Honrado, Mário Santos

Affiliations

  1. Fluvial Ecology Laboratory, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. Electronic address: [email protected].
  2. Laboratory of Applied Ecology, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. Electronic address: [email protected].
  3. Laboratory of Applied Ecology, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. Electronic address: [email protected].
  4. Fluvial Ecology Laboratory, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. Electronic address: [email protected].
  5. Centro de Investigacão em Biodiversidade e Recursos Genéticos (CIBIO), Faculdade de Ciências, Universidade do Porto, Porto, Portugal. Electronic address: [email protected].
  6. Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, The Netherlands. Electronic address: [email protected].
  7. Faculty of Earth and Life Sciences, VU University Amsterdam, De Boelelaan 1087, 1081 HV Amsterdam, The Netherlands; College of Resources and Environmental Sciences, China Agricultural University, 2 Yuanmingyuan W. Road, Haidian District, Beijing 100193, China. Electronic address: [email protected].
  8. Centro de Investigacão em Biodiversidade e Recursos Genéticos (CIBIO), Faculdade de Ciências, Universidade do Porto, Porto, Portugal. Electronic address: [email protected].
  9. Laboratory of Applied Ecology, CITAB - Centre for the Research and Technology of Agro-Environment and Biological Sciences, University of Trás-os-Montes e Alto Douro, Vila Real, Portugal. Electronic address: [email protected].

PMID: 27179681 DOI: 10.1016/j.scitotenv.2016.04.153

Abstract

This method development paper outlines an integrative stochastic dynamic methodology (StDM) framework to anticipate land use (LU) change effects on the ecological status of monitored and non-monitored lotic surface waters under the Water Framework Directive (WFD). Tested in the Alto Minho River Basin District in North West Portugal, the model is an innovative step towards developing a decision-making and planning tool to assess the influence impacts such as LU change and climate change on these complex systems. Comprising a series of sequential steps, a Generalized Linear Model based, competing model Multi Model Inference (MMI) approach was used for parameter estimation to identify principal land use types (distal factors) driving change in biological and physicochemical support elements (proximal factors) in monitored water bodies. The framework integrated MMI constants and coefficients of selected LU categories in the StDM simulations and spatial projections to simulate the ecological status of monitored and non-monitored lotic waterbodies in the test area under 2 scenarios of (1) LU intensification and (2) LU extensification. A total of 100 simulations were run for a 50year period for each scenario. Spatially dynamic projections of WFD metrics were obtained, taking into account the occurrence of stochastic wildfire events which typically occur in the study region and are exacerbated by LU change. A marked projected decline to "Moderate" ecological status for most waterbodies was detected under intensification but little change under extensification; only a few waterbodies fell to "moderate" status. The latter scenario describes the actual regional socio-economic situation of agricultural abandonment due to rural poverty, partly explaining the projected lack of change in ecological status. Based on the WFD "one out all out" criterion, projected downward shifts in ecological status were due to physicochemical support elements, namely increased phosphorus levels. Little or no change in status was driven by Intercalibrated Biological Quality Elements, indicating innate resilience and raising questions concerning uncertainty, the effect of pressures other than land use and metric redundancy and the WFD classification process.

Copyright © 2016 Elsevier B.V. All rights reserved.

Keywords: Ecological status; Land use change scenarios; Spatio-temporal projection; Stochastic dynamic methodology; Surface waterbodies; Water Framework Directive; Wildfire

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