2019 World Conference on Natural Resource Modelling

HEC Montréal, Canada, 22 — 24 May 2019

2019 World Conference on Natural Resource Modelling

HEC Montréal, Canada, 22 — 24 May 2019

Schedule Authors My Schedule

Case Studies 1

May 22, 2019 10:45 AM – 12:15 PM

Location: Banque CIBC

Chaired by Jean-Sauveur Ay

3 Presentations

  • 10:45 AM - 11:15 AM

    Multi-agent modeling, a lab for building sustainable management policies in coastal and marine ecosystems. The case of the Golfe du Lion Marine Park, results from the SAFRAN project

    • Elsa Mosseri, presenter, CIRED-CNRS
    • Catherine Boemare, CIRED-EHESS

    We modeled the Marine Park as a socio-ecological system and developed scenarios to 2050, inviting various stakeholders to build them. We considered mainly artificial reefs and offshore wind turbines facilities, phytoplankton variation and access and use rights as variables of sustainable management policies.
    The modeling approach is agent-based for looking at the evolution of supporting and regulating, recreational and provisioning services. Rocky and coral reefs, sands and posidonia habitats are placed at its core, specifying for each of them the trophic chain.
    Implementing scenarios revealed that access and use rights are the determining factors in the evolution of ecosystem services.

  • 11:15 AM - 11:45 AM

    Verification of GEM data in Iran using synoptic stations’ temperature and precipitation data

    • Abdolreza Bahremand, presenter, Gorgan University of Agricultural Sciences and Natural Resources
    • Mohammad Mohammadlou, Gorgan University of Agricultural Sciences and Natural Resources
    • Saman Razavi, University of Saskatchewan
    • Daniel Princz, Environment and Climate Change Canada

    The Global Environmental Multiscale Model (GEM) is an integrated forecasting and data assimilation system developed by Environment and Climate Change Canada. It is the operational model at the Canadian Meteorological Centre for weather forecasting. The model is currently operational for the global 25 km data assimilation cycle and medium-range forecasting, the regional 10 km data assimilation cycle and short-range forecasting over North America, and the high-resolution 2.5 km data assimilation cycle and short-range forecasting over Canada. In this research, the performance of the global forecast outputs werewas evaluated for the whole countryall of Iran (1,648,000 km2). Temperature and precipitation data generated by the global-scale GEM model are evaluated with 177 synoptic stations data in daily, monthly and yearly scale. The primary results using 7 synoptic stations located in Sefidrud River Basin (the second largest river in Iran with more than 60,000 km2 area) show that the GEM model performance has acceptable accuracy regarding rainfall and temperature. However, temperature data have a much better agreement with the observations than precipitation in the region.

  • 11:45 AM - 12:15 PM

    Disease dispersion as a spatial interaction : the case of grapevine flavescence dorée

    • Jean-Sauveur Ay, presenter, INRA

    Flavescence dorée is a severe vector-borne grapevine disease triggering quick death of the vine stock. It is transmitted exclusively by a leafhopper and has spread throughout France were it has become a serious issue (presently, it is a concern for more than half of French vineyards). Focusing on the spatial dissemination of FD, this paper investigates the private control and land-use strategies of heterogenous landowners, and their socially optimal counterparts. The theoretical model of individual decisions take into account strategic interactions among neighbors, as treatment and land use choices have consequences beyond a landowner’s plot. Using small-scale data of contamination and of mandatory pesticide application, the probability of being infected by FD is derived with a spatial econometrics specification.