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543 results for “larval development”
Fig. 1 in Effect Of Parental Care On The Duration Of Larval Development And Offspring Survival In Nicrophorus Mexicanus Matthews (Coleoptera: Silphidae)
Fig. 1. Differences in time development among the three experimental groups in N. mexicanus Mattews. 1.—Control group; 2.—Broodmass present and parents removed; 3.—Without parental care (brood mass not present and parents removed).
Fig. 2 in Effect Of Parental Care On The Duration Of Larval Development And Offspring Survival In Nicrophorus Mexicanus Matthews (Coleoptera: Silphidae)
Fig. 2. Differences between the number of adults emerged in each of the three experimental groups in N. mexicanus Matthews. 1.—Control group; 2.—Broodmass present and parents removed; 3.—Without parental care (brood mass not present and parents removed).
Ontogenetic variation in metabolic rate-temperature relationships during larval development
<p><span>Predictive models of ectotherm responses to environmental change often rely on thermal performance data from the literature. For insects, the majority of these data focus on two traits, development rate and thermal tolerance limits. Data are also often limited to the adult stage. Consequently, predictions based on these data generally ignore other measures of thermal performance and do not account for the role of ontogenetic variation in thermal physiology across the complex insect life cycle. Theoretical syntheses for predicting metabolic rate also make similar assumptions despite the strong influence of body size as well as temperature on metabolic rate. The aim of this study was to understand the influence of ontogenetic variation on ectotherm physiology and its potential impact on predictive modeling. To do this we examined metabolic rate-temperature (MR-T) relationships across the larval stage in a laboratory strain of the Spongy moth (<em>Lymantria dispar dispar</em>). Routine metabolic rates (RMR) of larvae were assayed at nine temperatures across the first five instars of the larval stage. After accounting for differences in body mass, larval instars showed significant variation in MR-T. Both the temperature sensitivity and allometry of RMR increased and peaked during the third instar, then declined in the fourth and fifth instar. Generally, these results show that insect thermal physiology does not remain static during larval ontogeny and suggest that ontogenetic variation should be an important consideration when modeling thermal performance.</span></p>
Field and Lab_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Field and Lab observations_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Depressions and Boundary_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Depressions and Boundary_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Aerial Images_Part 3_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Aerial Images_Part 3_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Orthomosaic_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Orthomosaic of the aerial images_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
DSM_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>DSM_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 11. Hymenosoma orbiculare Desmarest, 1825. Third maxilliped and pereiopods: (A) second zoea; (B) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 10. Hymenosoma orbiculare Desmarest, 1825. Dorsal view of the telson: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 8. Hymenosoma orbiculare Desmarest, 1825. Dorsal view of the abdomen: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.3 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 9. Hymenosoma orbiculare Desmarest, 1825. Lateral view of the abdomen: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.3 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 5. Hymenosoma orbiculare Desmarest, 1825. Maxilla: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 3. Hymenosoma orbiculare Desmarest, 1825. Antennule and antenna: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 2. Hymenosoma orbiculare Desmarest, 1825. Setation of ventral carapace margin: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 6. Hymenosoma orbiculare Desmarest, 1825. First maxilliped: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 4. Hymenosoma orbiculare Desmarest, 1825. Maxillule: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
F in The larval development of Hymenosoma orbiculare Desmarest, 1825 (Crustacea: Decapoda: Brachyura: Hymenosomatidae)
F. 7. Hymenosoma orbiculare Desmarest, 1825. Second maxilliped: (A) first zoea; (B) second zoea; (C) third zoea. Scale: 0.1 mm.
Density-by-diet interactions during larval development shape adult life-history trait expression and fitness in a polyphagous fly
<p><span>Habitat quality early in life determines individual fitness, with possible long-term evolutionary effects on groups and populations. In holometabolous insects, larval ecology plays a major role in determining the expression of traits in adulthood, but how ecological conditions during larval stage interact to shape adult life-history and fitness, particularly in non-model organisms, remains subject to scrutiny. Consequently, our knowledge of the interactive effects of ecological factors on insect development is limited. Here, using the polyphagous fly <i>Bactrocera tryoni</i>, we conducted a fully-factorial design where we manipulated larval density and larval diet (protein-rich, standard, and sugar-rich) to gain insights into how these ecological factors interact to modulate adult fitness. As expected, a protein-rich diet resulted in faster larval development, heavier and leaner adults that were more fecund compared with standard and sugar-rich diets, irrespective of larval density. Females from the protein-rich larval diet had overall higher reproductive rate (i.e., eggs per day) than females from other diets, and reproductive rate decreased linearly with density for females from the protein-rich but non-linearly for females from the standard and sugar-rich diets over time. Surprisingly, adult lipid reserve increased with larval density for adults from the sugar-rich diet (as opposed to decreasing, as in other diets), possibly due to a stress-response to an extremely adverse condition during development (i.e., high intraspecific competition and poor nutrition). Together, our results provide insights into how ecological factors early in life interact and shape the fate of individuals through life-stages in holometabolous insects. </span></p>
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