Main authors: Diana Sietz, Luuk Fleskens, Lindsay C. Stringer
Editor: Jane Brandt
Source document: Sietz, D. et al. (2017) Report on integrated modelling strategy. CASCADE Project Deliverable 8.2 33 pp


In this section of CASCADiS we have set out an integrated modelling strategy that uses scenario analysis and dynamic ecosystems understanding to generate recommendations for decision makers. This perspective on dynamic ecosystem regimes appraises actions that both foster restoration of degraded ecosystems and prevent degradation of functioning ecosystems. There is a high level of conceptual thinking embedded in ecological models, with model parameters that are not easily calibrated based on field data. In particular, there is an issue of scaling in going from conceptual 0-1 parameter values to indicator values that are observed in reality. In order to provide useful scenario output, an important step is to parametrise the model in such a way that it suitably represents the ecological conditions in a given study site. After successful parametrisation, the modelling strategy can be used to look for the spatial dimensions of best practices across gradients of environmental conditions (e.g. as a function of aridity index), livestock density and fodder price in the Mediterranean region.

The strategy offers three key lessons in operationalising LDN.

  • First, long-term field experiments are essential to strengthen advances in identifying dynamic ecosystem regimes including a variety of relevant ecosystem properties and developing reliable predictions of site-specific degradation and restoration drivers and outcomes. In particular, we call for probabilistic assessments of current ecosystem states in relation to stability domains and systematic use of early warning signals for predicting regime shifts to advance the spatial balancing of land degradation and recovery for achieving LDN.
  • Second, prediction of windows of opportunities and risks is essential to identify critical land management timings that realise ecological benefits at minimum risk and cost. Improved seasonal weather forecasts and ENSO early warnings can provide key information for such predictions, especially if packaged with restoration and SLM advice tailored to land users’ needs.
  • Third, successful multi-level LDN planning requires managerial flexibility that allows to continuously adapt investment decisions, including timing, to existing environmental conditions and ecosystem trajectories in relation to critical thresholds. This is a pre-requisite to rapidly take action once opportunities or risks emerge.

These insights into non-linear ecosystem dynamics help to better evaluate the effectiveness of land management options for achieving policy goals setting a positive trajectory for achievement of the Sustainable Development Goals and LDN.

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