The Experts below are selected from a list of 138 Experts worldwide ranked by ideXlab platform
Zuzanna Pietras - One of the best experts on this subject based on the ideXlab platform.
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Strong foraging preferences for Ribes alpinum (Saxifragales: Grossulariaceae) in the polyphagous caterpillars of Buff-tip moth Phalera bucephala (Lepidoptera: Notodontidae).
Ecology and evolution, 2020Co-Authors: Juliano Morimoto, Zuzanna PietrasAbstract:Herbivorous insects such as butterflies and moths are essential to natural and agricultural systems due to pollination and Pest Outbreaks. However, our knowledge of butterflies' and moths' nutrition is fragmented and limited to few common, charismatic, or problematic species.This gap precludes our complete understanding of herbivorous insects' natural history, physiological and behavioral adaptations that drive how species interact with their environment, the consequences of habitat fragmentation and climate change to invertebrate biodiversity, and Pest Outbreak dynamics.Here, we first report a population of the Buff-tip moth Phalera bucephala (Lepidoptera: Notodontidae) feeding on a previously unknown family of host plants, the mountain currant Ribes alpinum (Saxifragales: Grossulariaceae). This is the first report of a Notodontid moth feeding on Grossulariaceae hosts.Using no-choice and choice assays, we showed that P. bucephala has strong foraging preferences for a previously unknown hosts, the R. alpinum but also, although to a smaller extent, R. uva-crispa compared with a previously known host (the Norway maple Acer sp.).These findings demonstrate that P. bucephala feed on-and show strong preference for Grossulariaceae host plants, indicating flexible physiological mechanisms to accommodate hosts plants from various families. This makes this species a potential model organism to study the behavioral and physiological mechanisms underpinning insect-plant interactions and diet breadth evolution.We discuss the broad ecological implications of these observations to the biology of the species, the potential negative effects of interspecific competition with endemic specialist moths, and highlight questions for future research.
Juliano Morimoto - One of the best experts on this subject based on the ideXlab platform.
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Strong foraging preferences for Ribes alpinum (Saxifragales: Grossulariaceae) in the polyphagous caterpillars of Buff-tip moth Phalera bucephala (Lepidoptera: Notodontidae).
Ecology and evolution, 2020Co-Authors: Juliano Morimoto, Zuzanna PietrasAbstract:Herbivorous insects such as butterflies and moths are essential to natural and agricultural systems due to pollination and Pest Outbreaks. However, our knowledge of butterflies' and moths' nutrition is fragmented and limited to few common, charismatic, or problematic species.This gap precludes our complete understanding of herbivorous insects' natural history, physiological and behavioral adaptations that drive how species interact with their environment, the consequences of habitat fragmentation and climate change to invertebrate biodiversity, and Pest Outbreak dynamics.Here, we first report a population of the Buff-tip moth Phalera bucephala (Lepidoptera: Notodontidae) feeding on a previously unknown family of host plants, the mountain currant Ribes alpinum (Saxifragales: Grossulariaceae). This is the first report of a Notodontid moth feeding on Grossulariaceae hosts.Using no-choice and choice assays, we showed that P. bucephala has strong foraging preferences for a previously unknown hosts, the R. alpinum but also, although to a smaller extent, R. uva-crispa compared with a previously known host (the Norway maple Acer sp.).These findings demonstrate that P. bucephala feed on-and show strong preference for Grossulariaceae host plants, indicating flexible physiological mechanisms to accommodate hosts plants from various families. This makes this species a potential model organism to study the behavioral and physiological mechanisms underpinning insect-plant interactions and diet breadth evolution.We discuss the broad ecological implications of these observations to the biology of the species, the potential negative effects of interspecific competition with endemic specialist moths, and highlight questions for future research.
Louis De Grandpre - One of the best experts on this subject based on the ideXlab platform.
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model specification uncertainty in future forest Pest Outbreak
Global Change Biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
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Model‐specification uncertainty in future forest Pest Outbreak
Global change biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
Yan Boulanger - One of the best experts on this subject based on the ideXlab platform.
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model specification uncertainty in future forest Pest Outbreak
Global Change Biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
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Model‐specification uncertainty in future forest Pest Outbreak
Global change biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
Barry J Cooke - One of the best experts on this subject based on the ideXlab platform.
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model specification uncertainty in future forest Pest Outbreak
Global Change Biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
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Model‐specification uncertainty in future forest Pest Outbreak
Global change biology, 2016Co-Authors: Yan Boulanger, Barry J Cooke, David R Gray, Louis De GrandpreAbstract:Climate change will modify forest Pest Outbreak characteristics, although there are disagreements regarding the specifics of these changes. A large part of this variability may be attributed to model specifications. As a case study, we developed a consensus model predicting spruce budworm (SBW, Choristoneura fumiferana [Clem.]) Outbreak duration using two different predictor data sets and six different correlative methods. The model was used to project Outbreak duration and the uncertainty associated with using different data sets and correlative methods (=model-specification uncertainty) for 2011-2040, 2041-2070 and 2071-2100, according to three forcing scenarios (RCP 2.6, RCP 4.5 and RCP 8.5). The consensus model showed very high explanatory power and low bias. The model projected a more important northward shift and decrease in Outbreak duration under the RCP 8.5 scenario. However, variation in single-model projections increases with time, making future projections highly uncertain. Notably, the magnitude of the shifts in northward expansion, overall Outbreak duration and the patterns of Outbreaks duration at the southern edge were highly variable according to the predictor data set and correlative method used. We also demonstrated that variation in forcing scenarios contributed only slightly to the uncertainty of model projections compared with the two sources of model-specification uncertainty. Our approach helped to quantify model-specification uncertainty in future forest Pest Outbreak characteristics. It may contribute to sounder decision-making by acknowledging the limits of the projections and help to identify areas where model-specification uncertainty is high. As such, we further stress that this uncertainty should be strongly considered when making forest management plans, notably by adopting adaptive management strategies so as to reduce future risks.
