The application of degree-day models to study current and future organism development: cautions, limitations, and recommendations Pubblico
Moore, Julia L (2011)
Published
Abstract
Degree-day models are mathematical models that have been used
extensively to
study organism development, particularly in agricultural and public
health contexts.
Though simple and easy to use, model specifications and parametric
uncertainty can
influence the results of such applications, often substantially.
Yet, model limitations
and assumptions are often not considered in the application of
degree-day models.
This thesis investigates the structural and parametric choices that
must be made
when using degree-day models, and makes recommendations for how
these models
can best be applied. First, degree-day model structure and
assumptions are
comprehensively reviewed. In particular, linear and non-linear
developmental
functional responses are compared, as are the various methods used
to incorporate
temperature thresholds and to calculate daily degree-days. Next,
uncertainty in two
key degree-day model parameters is explored by using a population
model of
Oncomelania hupensis, the intermediate snail host of the parasite
that causes
schistosomiasis in East Asia, to make predictions of future snail
distributions in
Sichuan Province, China. I conclude that structural and parametric
specifications
should be chosen based on the context of the organism under study
and the specific
temperature patterns of the region. In addition, future predictions
of organism
distribution are highly sensitive to parametric uncertainty, and
thus caution should
be used when interpreting the results of degree-day model
predictions under
scenarios of future climate change. I conclude that, if degree-day
model limitations
are considered and model assumptions met, degree-day models can be
a powerful
tool for studying temperature-dependent development.
Table of Contents
Introduction
Chapter 1. Modeling temperature-dependent development: structural, parametric, and experimental issues in degree-day models
1.1. Introduction
1.2. Generalized model of temperature-dependent development
1.3. Developmental functional response
1.3.1. Linear
1.3.2. Non-linear
1.3.3. Comparison of functional response forms
1.4. Temperature thresholds
1.4.1. Estimating temperature thresholds
1.5. Degree-days
1.5.1. Estimating teh total degree-days required for development, K
1.5.2. Methods for calculating daily degree-days, k
1.5.2.1. Daily average
1.5.2.2. Triangle and double triangle
1.5.2.3. Sine and double sine
1.5.2.4. Variations
1.5.3. Comparison of methods used to calculate k
1.6. Discussion
Chapter 2. Cautioning the use of degree-day models for licmate change projections: predicting the future distribution of parasite hosts in the presence of parametric uncertainty
2.1. Introduction
2.2. Materials and methods
2.2.1. Population model
2.2.2. Temperature data
2.2.3. Parameter estimation using historical Oncomelania hupensis
presence in Sichuan Province
2.2.4. Sensitivity analysis
2.2.4.1. Individual location analysis
2.2.4.1. Distributional analysis
2.3. Results
2.3.1. Temperature projection model
2.3.2. Parameter estimation
2.3.3. Sensitivity analysis
2.3.3.1. Individual cell analysis
2.3.3.2. Distributional analysis
2.4. Discussion
2.5. Conclusion
2.6. Acknowledgements
Conclusion
Bibliography
About this Master's Thesis
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