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Mathematics and Statistics Group

Seminar Programme: Winter/Spring 2017/2018 - ALL WELCOME

All seminars take place on Tuesdays at 3pm in the Cottrell Building, room 4B96 (Except where stated otherwise).

For further details please contact:

Date Speaker Title
29th Aug - Room 2B38
Dr. Shadi Atallah

University of New Hampshire
The bio-economics of managing invasive plant externalities in forests with heterogeneous landowner preferences
Forest invasive plants can cause market (MES) and non-market ecosystem service (NMES) losses to private forest landowners. Because the bio-invasion creates spatial-dynamic ecological-economic linkages among landowners, bio-invasion control is a weaker-link public good and is likely to be underprovided. We hypothesize that heterogeneity in forest landowner preferences is a major determinant of bio-invasion spatial externalities. To test this hypothesis, we develop a spatial-dynamic model of bio-invasion and control with two agents that value differently the MES and NMES produced by the forest. Landowners choose control strategies and ignore the impact of their decisions on their neighbors. In the absence of long-distance dispersal, they both control the bio-invasion regardless of their preferences. In the presence of long-distance dispersal, a central planner controls the bio-invasion as well. However, when landowners have heterogeneous preferences, the MES landowner implements bio-invasion control, but the NMES landowner does not, creating a wedge between the central planner and decentralized management solutions. We compare uniform and non-uniform payments for ecosystem services (PES) and find that a PES to the NMES landowner is enough to mitigate the externality whereas a non-uniform PES is costlier and leads to a non-additional participation of the MES landowner.


NB: This seminar will be in Room 2B38.
19th Sept
Dr. Brad Duthie
‌BES
University of Stirling
GMSE: a general tool for management strategy evaluation
Management strategy evaluation (MSE) is a powerful tool for simulating all key aspects of natural resource management under conditions of uncertainty. Here I present the R package GMSE, which generalises MSE using a game-theoretic approach to simulate adaptive decision-making management scenarios between stakeholders with competing objectives under complex social-ecological interactions and uncertainty. GMSE is agent-based and spatially explicit, and incorporates a high degree of realism through mechanistic modelling of links and feedbacks among stakeholders and with the ecosystem. I demonstrate how GMSE simulates a social-ecological system using the example of a waterfowl population in an agricultural landscape that is adaptively managed; simulated waterfowl exploit agricultural land, causing conflict between conservation interests and the interest of food producers maximising their crop yield. The R package GMSE is open source under GNU Public License; source code and documents are freely available on GitHub.
3rd Oct
Dr. Craig Tennenhouse
‌Mathematics
University of New England
TBA
TBA
31st Oct
Dr. Paul Johnson
‌Institute of Biodiversity, Animal Health, and Comparative Medicine
University of Glasgow
TBA
TBA
14th Nov
Prof. Rachel Norman
‌CSM
University of Stirling
TBA
TBA
21st Nov
Dr. Scott Denholm
‌Animal & Veterinary Sciences Research Group
SRUC
TBA
TBA
28th Nov
Dr. Paul McMenemy
‌CS&M
University of Stirling
TBA
TBA

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