Comparative Temperature-Dependent Development ofNephus includens(Kirsch) andNephus bisignatus(Boheman) (Coleoptera: Coccinellidae) Preying onPlanococcus citri(Risso) (Homoptera: Pseudococcidae): Evaluation of a Linear and Various Nonlinear Models Using Specific Criteria

Kontodimas, D. C.; Eliopoulos, Panagiotis A.; Stathas, G. J.; Economou, Leonidas

doi:10.1603/0046-225x-33.1.1

Cited by 247 publications

(76 citation statements)

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“…The linear model is thus best applied when environmental temperatures fall within intermediate temperature ranges for which the linear approximation is valid (Bonhomme 2000; Bergant and Trdan 2006). Since organisms routinely experience temperature extremes well outside these intermediate ranges, several non-linear models have been developed as alternative functional forms of f (Kontodimas et al 2004). …”

Section: Methodsmentioning

confidence: 99%

“…To estimate δ max and δ opt , non-linear developmental models are generally used (Roy et al 2002; Kontodimas et al 2004). For many non-linear models, these thresholds appear explicitly within the model equation, and thus can be estimated using non-linear regression (e.g.…”

Section: Methodsmentioning

confidence: 99%

“…Thus, despite the fact that limited field emergence time data exist with which to interpret model predictions, we chose N. bisignatus because its developmental response to temperature has been characterized in great detail through laboratory experiments. Model parameters were drawn from previous experimental work (Kontodimas et al 2004) that fit linear and non-linear models to developmental data from laboratory studies in which N. bisignatus were reared at various constant temperatures. Where previously fit models could not provide estimates of δ min or δ max , the lower and upper rearing temperatures at which no development occurred (10 ºC and 35 ºC, respectively) were used.…”

Section: Methodsmentioning

confidence: 99%

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Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues

Moore

Remais

2014

Acta Biotheor

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Developmental models that account for the metabolic effect of temperature variability on poikilotherms, such as degree-day models, have been widely used to study organism emergence, range and development, particularly in agricultural and vector-borne disease contexts. Though simple and easy to use, structural and parametric issues can influence the outputs of such models, often substantially. Because the underlying assumptions and limitations of these models have rarely been considered, this paper reviews the structural, parametric, and experimental issues that arise when using degree-day models, including the implications of particular structural or parametric choices, as well as assumptions that underlie commonly used models. Linear and nonlinear developmental functions are compared, as are common methods used to incorporate temperature thresholds and calculate daily degree-days. Substantial differences in predicted emergence time arose when using linear vs. non-linear developmental functions to model the emergence time in a model organism. The optimal method for calculating degree-days depends upon where key temperature threshold parameters fall relative to the daily minimum and maximum temperatures, as well as the shape of the daily temperature curve. No method is shown to be universally superior, though one commonly used method, the daily average method, consistently provides accurate results. The sensitivity of model projections to these methodological issues highlights the need to make structural and parametric selections based on a careful consideration of the specific biological response of the organism under study, and the specific temperature conditions of the geographic regions of interest. When degree-day model limitations are considered and model assumptions met, the models can be a powerful tool for studying temperature-dependent development.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues

Moore

Remais

2014

Acta Biotheor

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“…There are various methods and models (i.e., see Sharpe et al 1977;Pruess 1983;Wagner et al 1984a;Kontodimas et al 2004;Van der Have 2008;Damos and Savopoulou-Soultani 2012), but for the reason of brevity, we will mention only the two most common approaches applied in entomology: the physiological time concept and empirical regressions between accumulated degree-days and cumulative population emergence.…”

Section: Introductionmentioning

confidence: 99%

Modular structure of web-based decision support systems for integrated pest management. A review

Damos

2015

Agron. Sustain. Dev.

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Sustainable pest management implies less pesticide use and replacement by safe control alternatives. This requires decision support for rational pest management. However, in practice, successful decision making is dependent upon the availability of integrated, high-quality information. Computer-aided forecasting and related decision support systems make pest control more sustainable by avoiding unwanted consequences of pesticide applications. Here, I review integrated pest management for web-based decision support systems. The major points are the following: (1) Principles of integrated pest management are compatible with sustainable agriculture. (2) Pest models serve as basis of decision making because they offer means to predict the exact time of pest phenological development and initiate management actions. Most models are climate driven. (3) New hardware technology has permitted the registration of automatically recorded climatic data. This data can be combined with pest models through logical operations and forecasting algorithms to develop a software of pest management. (4) Dynamic web interfaces can serve as decision support systems providing the user with real-time pest warnings and recommendations for management actions. (5) Ontology web programing and semantic knowledge representations provide a way to classify and describe agrodata to facilitate information sharing and data exploitation over distributed systems. (6) Most available pest management data is published on static web pages and, thus, cannot be classified as decision support systems. Some web-based decision support systems provide user-interactive content and real-time pest forecasts and management support.

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“…These non-linear models are like a two-sided sword: (1) they represent abundant tools for describing the temperature-dependent development rates; (2) it takes to spend much time on choosing one among so many models. Although some comparative studies were done to recommend the best of these models (e.g., Smits et al 2003;Kontodimas et al 2004;Kim et al 2009;Shi & Ge 2010), these studies did not draw a corresponding conclusion yet.…”

mentioning

confidence: 99%

Using the loess method to describe the effect of temperature on development rate

Liu¹,

Yan²,

Mingfu³

et al. 2017

Plant Prot. Sci.

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Liu J., Yan Y., Yu M., Parajulee † M.N., Shi P., Liu J., Zhao Z. (2017): Using the LoeSS method to describe the effect of temperature on development rate. Plant Protect. Sci., 53: 226-231.Temperature has a significant influence on development rates of insects and mites. Many parametric models were built to describe the temperature-dependent development rates. However, these models provided different shapes of the curves of development rate versus temperature. For different datasets, investigators have to spend much time on considering which the parametric model is the best for describing the temperature-dependent development rates. In the present study, we encourage investigators to use an important non-parametric model, the LoeSS method, which belongs to local regression methods. The LoeSS method is used to fit some published data on the development rate of aphids to check the goodness-of-fit. We find that the LoeSS method is very flexible for fitting the given datasets. Thus, we consider that the LoeSS method can be used to describe the effect of temperature on the development rate of insects or mites.Keywords: non-parametric model; local regression; weighted least squares; AphididaeIn general, one insect or mite species needs to experience different developmental stages in its lifecycle. Completing each developmental stage requires a period of time, which is referred to as development time (or development duration). The reciprocal characteristic of development time is referred to as development rate. It has been demonstrated that temperature has a strong influence on development rate (Campbell et al. 1974;Taylor 1981). Development rate is regarded as a linear function of temperature over the range of moderate temperatures (Campbell et al. 1974;Zhao et al. 2012). However, this linear relationship between development rate and temperature does not fit if temperatures were not in this range. Several non-linear models have been developed for describing the effect of temperature on development rate (e.g., Logan et al.

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Comparative Temperature-Dependent Development ofNephus includens(Kirsch) andNephus bisignatus(Boheman) (Coleoptera: Coccinellidae) Preying onPlanococcus citri(Risso) (Homoptera: Pseudococcidae): Evaluation of a Linear and Various Nonlinear Models Using Specific Criteria

Cited by 247 publications

References 58 publications

Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues

Developmental Models for Estimating Ecological Responses to Environmental Variability: Structural, Parametric, and Experimental Issues

Modular structure of web-based decision support systems for integrated pest management. A review

Using the loess method to describe the effect of temperature on development rate

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