Degday: A Program for Calculating Degree-days, and Assumptions Behind the Degree-day Approach

Higley, Leon G.; Pedigo, Larry P.; Ostlie, K. R.

doi:10.1093/ee/15.5.999

Cited by 263 publications

(219 citation statements)

References 18 publications

(30 reference statements)

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“…Abiotic factors, in particular, temperature can directly affect the growth of poikilotherms, such as fish (Atkinson, 1994;Kitchell et al, 1977;van der Have and de Jong, 1996) by influencing enzymatic activity, and therefore, metabolic rates (Higley et al, 1986).…”

Section: Introductionmentioning

confidence: 99%

Degree-day accumulation influences annual variability in growth of age-0 walleye

et al. 2013

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a b s t r a c tThe growth of age-0 fishes influences survival, especially in temperate regions where size-dependent over-winter mortality can be substantial. Additional benefits of earlier maturation and greater fecundity may exist for faster growing individuals. This study correlated prey densities, growing-degree days, water-surface elevation, turbidity, and chlorophyll a with age-0 walleye Sander vitreus growth in a southcentral Nebraska irrigation reservoir. Growth of age-0 walleye was variable between 2003 and 2011, with mean lengths ranging from 128 to 231 mm by fall (September 30th-October 15th). A set of a priori candidate models were used to assess the relative support of explanatory variables using Akaike's information criterion (AIC). A temperature model using the growing degree-days metric was the best supported model, describing 65% of the variability in annual mean lengths of age-0 walleye. The second and third best supported models included the variables chlorophyll a (r 2 = 0.49) and larval freshwater drum density (r 2 = 0.45), respectively. There have been mixed results concerning the importance of temperature effects on growth of age-0 walleye. This study supports the hypothesis that temperature is the most important predictor of age-0 walleye growth near the southwestern limits of its natural range.

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Section: Introductionmentioning

confidence: 99%

Degree-day accumulation influences annual variability in growth of age-0 walleye

et al. 2013

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“…Embora a previsão de ocorrência, com base na temperatura do solo, tenha diferido da época observada, os erros foram de apenas 10,1 e 12,2%, considerando-se, respectivamente, as temperaturas registradas e estimadas (Tabela 2). Segundo Higley et al (1986), esta margem de erro é tolerável, já que em modelos de graus-dia que possibilitem previsões de ocorrência com 10% a 15% de imprecisão são ainda considerados adequados para a tomada de decisão no manejo de pragas. Com base nesse princípio, pode-se afirmar que as temperaturas do solo (registradas ou estimadas) podem ser utilizadas para prever a ocorrência de D. speciosa, utilizando o modelo de graus-dia de laboratório, enquanto a temperatura do ar não se adequaria para tal previsão.…”

Section: Resultsunclassified

Previsão de ocorrência de Diabrotica speciosa utilizando-se o modelo de graus-dia de laboratório

Ávila

Milanez

Parra³

2002

Pesq. agropec. bras.

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Resumo Foram determinadas, neste trabalho, as exigências térmicas (graus-dia) e a previsão de ocorrência de adultos de Diabrotica speciosa (Coleoptera: Chrysomelidae) em condições de campo (telado). Empregaram-se as temperaturas do solo e do ar no modelo linear de graus-dia, determinado para o inseto em condições de laboratório. O número de graus-dia acumulados para o desenvolvimento de D. speciosa foi determinado efetuando-se o somatório diário de unidades térmicas, a partir da temperatura-base de desenvolvimento (11,04ºC), utilizando-se, como dieta de larvas, raízes de milho cultivado em vasos. O valor da constante térmica (K) foi empregado para determinar a previsão de ocorrência do inseto, com base nas temperaturas médias do solo e do ar, registradas durante o período experimental. Independentemente do ambiente em que a temperatura foi registrada (ar ou solo), os valores de graus-dia acumulados para o desenvolvimento de D. speciosa foram significativamente inferiores ao valor de K obtido no laboratório. As temperaturas do solo (registradas ou estimadas a partir da do ar) e a do ar proporcionaram uma previsão de ocorrência do inseto significativamente diferente da observada experimentalmente. Todavia, a previsão de ocorrência com base na temperatura do ar foi mais discrepante em relação à observada experimentalmente, do que quando as temperaturas do solo (registradas ou estimadas) foram empregadas.Termos para indexação: insetos, temperatura, etapas de desenvolvimento animal, controle de pragas. Prediction of occurrence of Diabrotica speciosa using the laboratory degree-day modelAbstract The goal of this work was to determine the thermal requirements (degree-day) and the prediction of occurrence of adults of Diabrotica speciosa (Coleoptera: Chrysomelidae) under field conditions (screenhouse). The soil and air temperatures were used in a linear model of degree-day, determined for the insect under laboratory conditions. Thermal requirements for the development of D. speciosa were determined by the daily accumulation of thermal units (degree-day), starting from the base development temperature of the insect (11.04ºC), using corn roots cultivated in pots as larvae diet. The value of the thermal constant (K) was used to predict insect occurrence, based on the mean temperatures of the soil and the air recorded during the experimental period. Regardless of the kind of temperature (air or soil) employed for the thermal requirements accounting, the accumulated degreeday values for the development of D. speciosa were significantly lower than the K value achieved in the laboratory. The soil or air temperatures provided a forecast of occurrence of the insect significantly different from that observed experimentally. Nevertheless, the occurrence forecast based in the air temperature was less accurate than when the soil temperatures (registered or estimated) were used.

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“…In fact, the occurrence of arthropods under field conditions may be observed before or after the predicted date, and these differences may be associated with errors in the lower temperature threshold (Tb) and thermal constant (k) estimates. Thus, degree-day models are considered adequate to be used in pest management programs if they predict the occurrence of a pest within a margin of error of up to two days (MORALES; HOWER, 1981, WEST;LAING, 1984, HIGLEY et al, 1986CIVIDANES;BERNAL;GONZÁLEZ, 1993;FIGUEIREDO, 1997). Ávila et al (2002) observed that degree-day values accumulated during development of the coleopteran Diabrotica speciosa (Chrysomelidae), an agricultural pest, under field conditions, due to fluctuating soil and air temperatures were different from values obtained in the laboratory conditions where constant temperatures were used.…”

Section: Discussionmentioning

confidence: 99%

“…The results of these studies, in degree-days, have aided the development of models, which have been used in Integrated Pest Management programs, so as to predict the occurrence of population peaks under field conditions, and determine the most adequate period for sampling and control measures, providing a better understanding about population dynamics of pest insects and their natural enemies (WEST;LAING, 1984;HIGLEY et al, 1986;MILLER, 1992).…”

Section: Introductionmentioning

confidence: 99%

Thermal requirements of Dermanyssus gallinae (De Geer, 1778) (Acari: Dermanyssidae)

Tucci¹,

Prado

Araújo³

2008

Rev. Bras. Parasitol. Vet.

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The thermal requirements for development of Dermanyssus gallinae were studied under laboratory conditions at 15, 20, 25, 30 and 35°C, a 12h photoperiod and 60-85% RH. The thermal requirements for D. gallinae were as follows. Preoviposition: base temperature 3.4ºC, thermal constant (k) 562.85 degree-hours, determination coefficient (R²) 0.59, regression equation: Y= -0.006035 + 0.001777 x. Egg: base temperature 10.60ºC, thermal constant (k) 689.65 degree-hours, determination coefficient (R²) 0.94, regression equation: Y= -0.015367 + 0.001450 x. Larva: base temperature 9.82ºC, thermal constant (k) 464.91 degree-hours, determination coefficient R² 0.87, regression equation: Y= -0.021123+0.002151 x. Protonymph: base temperature 10.17ºC, thermal constant (k) 504.49 degree-hours, determination coefficient (R²) 0.90, regression equation: Y= -0.020152 + 0.001982 x. Deutonymph: base temperature 11.80ºC, thermal constant (k) 501.11 degree-hours, determination coefficient (R²) 0.99, regression equation: Y= -0.023555 + 0.001996 x. The results obtained showed that 15 to 42 generations of Dermanyssus gallinae may occur during the year in the State of São Paulo, as estimated based on isotherm charts. Dermanyssus gallinae may develop continually in the State of São Paulo, with a population decrease in the winter. There were differences between the developmental stages of D. gallinae in relation to thermal requirements.
Experimentos de laboratório foram realizados visando estimar as exigências térmicas de Dermanyssus gallinae. Para isso, o desenvolvimento do ácaro foi estudado em condições de laboratório usando-se câmaras climatizadas reguladas a 15, 20, 25, 30 e 35°C, fotofase de 12h e UR de 6085%. As exigências térmicas determinadas para D. gallinae foram: Pré-oviposição: temperatura base de 3,4 ºC, constante térmica (k) igual a 562,85 graus-hora, coeficiente de determinação (R²) igual a 0,59, equação de regressão: Y= -0,006035 + 0,001777 x. Ovo. Temperatura base de 10,60 ºC, constante térmica (k) igual a 689,65 graus-hora, coeficiente de determinação (R²) igual a 0,94, equação de regressão: Y= -0,015367 + 0,001450 x. Larva. Temperatura base 9,82 ºC, constante térmica (k) igual a 464,91 graus-hora, R² igual a 0,87, equação de regressão: Y= -0,021123+0,002151x. Protoninfa. Temperatura de 10,17 ºC, constante térmica (k) igual a 504,49 graus-hora, coeficiente de determinação (R²) igual a 0,90, equação de regressão: Y= -0,020152 + 0,001982 x. Deutoninfa. Temperatura de 11,80 ºC, constante (k) térmica igual a 501,11 graus-hora, coeficiente de determinação (R²) igual a 0,99, equação de regressão: Y= -0,023555 + 0,001996 x. Os resultados obtidos permitem concluir que no Estado de São Paulo podem ocorrem de 15 a 42 gerações/ano de D. gallinae, em estimativa baseada em isotermas. Dermanyssus gallinae pode se desenvolver continuamente no Estado de São Paulo, com diminuição da população no inverno. Existem diferenças entre os estágios de desenvolvimento de D. gallinae com relação às exigências térmicas

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Degday: A Program for Calculating Degree-days, and Assumptions Behind the Degree-day Approach

Cited by 263 publications

References 18 publications

Degree-day accumulation influences annual variability in growth of age-0 walleye

Degree-day accumulation influences annual variability in growth of age-0 walleye

Previsão de ocorrência de Diabrotica speciosa utilizando-se o modelo de graus-dia de laboratório

Thermal requirements of Dermanyssus gallinae (De Geer, 1778) (Acari: Dermanyssidae)

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