scholarly journals Qualitative Modeling for Bridging Expert-Knowledge and Social-Ecological Dynamics of an East African Savanna

Land ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 42
Author(s):  
Maximilien Cosme ◽  
Christelle Hély ◽  
Franck Pommereau ◽  
Paolo Pasquariello ◽  
Christel Tiberi ◽  
...  
Keyword(s):  
Dynamic Modeling ◽  
Expert Knowledge ◽  
Discrete Event ◽  
Quantitative Information ◽  
Qualitative Modeling ◽  
East African ◽  
Modeling Framework ◽  
African Savanna ◽  
Social Ecological ◽  
Economic Transitions

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modeling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modeling frameworks have proved useful for explaining ecosystem responses to perturbations, while only requiring qualitative information about social-ecological interactions and events and providing more general predictions due to their validity for wide ranges of parameter values. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modeling framework based on “if-then” rules generating non-deterministic dynamics. Based on expert knowledge, observations, and literature, we use EDEN to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups have highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modeling.

scholarly journals Qualitative Modelling for Bridging Expert-Knowledge and the Social-Ecological Dynamics of an East African Savanna

2021 ◽  
Author(s):  
Maximilien Cosme ◽  
Christelle Hély ◽  
Franck Pommereau ◽  
Paolo Pasquariello ◽  
Christel Tiberi ◽  
...  
Keyword(s):  
Expert Knowledge ◽  
Discrete Event ◽  
Management Strategies ◽  
Dynamic Modelling ◽  
Quantitative Information ◽  
East African ◽  
African Savanna ◽  
Qualitative Modelling ◽  
Social Ecological ◽  
Economic Transitions

Sub-Saharan social-ecological systems are undergoing changes in environmental conditions, including modifications in rainfall pattern and biodiversity loss. Consequences of such changes depend on complex causal chains which call for integrated management strategies whose efficiency could benefit from ecosystem dynamic modelling. However, ecosystem models often require lots of quantitative information for estimating parameters, which is often unavailable. Alternatively, qualitative modelling frameworks have proved useful for explaining ecosystem response to perturbations, while requiring fewer information and providing more general predictions. However, current qualitative methods have some shortcomings which may limit their utility for specific issues. In this paper, we propose the Ecological Discrete-Event Network (EDEN), an innovative qualitative dynamic modelling framework based on "if-then" rules which generates many alternative event sequences (trajectories). Based on expert knowledge, observations and literature, we use this framework to assess the effect of permanent changes in surface water and herbivores diversity on vegetation and socio-economic transitions in an East African savanna. Results show that water availability drives changes in vegetation and socio-economic transitions, while herbivore functional groups had highly contrasted effects depending on the group. This first use of EDEN in a savanna context is promising for bridging expert knowledge and ecosystem modelling.

scholarly journals East-African savanna dynamics: from a knowledge-based model to the possible futures of a social-ecological system

2021 ◽  
Author(s):  
Maximilien Cosme ◽  
Christelle Hély ◽  
Franck Pommereau ◽  
Paolo Pasquariello ◽  
Christel Tiberi ◽  
...  
Keyword(s):  
Local Knowledge ◽  
Discrete Event ◽  
Rangeland Management ◽  
Ecosystem Dynamics ◽  
Decision Makers ◽  
Bush Encroachment ◽  
Vegetation Types ◽  
East African ◽  
Pastoral Systems ◽  
African Savanna

Sub-Saharan savanna ecosystems are undergoing transitions such as bush encroachment, desertification or agricultural expansion. Such shifts and persistence of land cover are increasingly well understood, especially bush encroachment which is of major concern in pastoral systems. Although dominant factors can explain such transformations, they often result from intertwined causes in which human activities play a significant role. Therefore, in this latter case, these issues may require integrated solutions, involving many interacting components. Ecosystem modelling has proved appropriate to support decision-makers in such complex situations. However, ecosystem models often require lots of quantitative information for estimating parameters and the precise functional form of interactions is often unknown. Alternatively, in rangeland management, States-and-Transitions Models (STMs) have been developed to organize knowledge about system transitions and to help decision-makers. However, these conceptual diagrams often lack mathematical analyzing tools, which strongly constrains their complexity. In this paper, we introduce the Ecological Discrete-Event Network (EDEN) modelling approach for representing the qualitative dynamics of an East-African savanna as a set of discrete states and transitions generated from empirical rules. These rules are derived from local knowledge, field observations and scientific literature. In contrast with STMs, EDEN generates automatically every possible states and transitions, thus enabling the prediction of novel ecosystem structures. Our results show that the savanna is potentially resilient to the disturbances considered. Moreover, the model highlights all transitions between vegetation types and socio-economic profiles under various climatic scenarios. The model also suggests that wildlife diversity may increase socio-economic resistance to seasonal drought. Tree-grass coexistence and agropastoralism have the widest ranges of conditions of existence of all vegetation types and socio-economic profiles, respectively. As this is a preliminary use of EDEN for applied purpose, analysis tools should be improved to enable finer investigation of desirable trajectories. By translating local knowledge into ecosystem dynamics, the EDEN approach seems promising to build a new bridge between managers and modellers.

Density dependence and the spread of invasive big-headed ants (Pheidole megacephala) in an East African savanna

Oecologia ◽  
2021 ◽  
Author(s):  
Alejandro G. Pietrek ◽  
Jacob R. Goheen ◽  
Corinna Riginos ◽  
Nelly J. Maiyo ◽  
Todd M. Palmer
Keyword(s):  
Density Dependence ◽  
East African ◽  
African Savanna ◽  
Pheidole Megacephala

System Level Dynamic Modeling Framework Being Developed at Clemson University’s Wind Turbine Drivetrain Testing Facility

2013 ◽  
Author(s):  
Ryan Schkoda ◽  
Konstantin Bulgakov ◽  
Kalyan Chakravarthy Addepalli ◽  
Imtiaz Haque
Keyword(s):  
Wind Turbine ◽  
Dynamic Modeling ◽  
Preliminary Analysis ◽  
Collaborative Work ◽  
Model Development ◽  
System Level ◽  
Modeling Framework ◽  
Testing Facility ◽  
Simulation Strategy ◽  
North Charleston

This paper describes the system level, dynamic modeling and simulation strategy being developed at the Wind Turbine Drivetrain Testing Facility (WTDTF) at Clemson University’s Restoration Institute in North Charleston, SC, USA. An extensible framework that allows various workflows has been constructed and used to conduct preliminary analysis of one of the facility’s test benches. The framework dictates that component and subsystem models be developed according to a list of identified needs and modeled in software best suited for the particular task. Models are then integrated according to the desired execution target. This approach allows for compartmentalized model development which is well suited for collaborative work. The framework has been applied to one of the test benches and has allowed researches to begin characterizing its behavior in the time and frequency domain.

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