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9 results for “invasiveness forecast”
Fig. 4 in Forecasting the impact of an invasive macrophyte species in the littoral zone through aquatic insect species composition
Fig. 4. Comparison among Bray-Curtis dissimilarity indices of aquatic insect assemblages associated with white ginger lily banks and native vegetation profile in the littoral zone of a tropical reservoir in the Brazilian Savanna (Group 1, white ginger lily; Group 2, invaded forest; Group 3, native macrophyte; Group 4, riparian vegetation).
Fig. 2 in Forecasting the impact of an invasive macrophyte species in the littoral zone through aquatic insect species composition
Fig. 2. Comparison between ecological variables of aquatic insect assemblages associated with invasive white ginger lily bank and other native vegetation banks in the littoral zone of a tropical reservoir in the Brazilian Savanna (A, abundance; B, richness; C, Simpson diversity; IM, invasive macrophyte; IF, invaded forest; NM, native macrophyte; RV, riparian vegetation).
Fig. 1 in Forecasting the impact of an invasive macrophyte species in the littoral zone through aquatic insect species composition
Fig. 1. Location and characterization of vegetation profile banks of the Fazzari reservoir in the Brazilian Savanna (Cerrado Biome, Brazil).
Fig. 3 in Forecasting the impact of an invasive macrophyte species in the littoral zone through aquatic insect species composition
Fig. 3. Analyses of non-metric MDS of aquatic insect assemblages associated with white ginger lilY banks and native vegetation profiles in the littoral zone of a tropical reservoir in the Brazilian Savanna (●, white ginger lilY; ○, invaded forest; ∆, native macrohYte; ▲, riparian vegetation).
Forecasting suppression of invasive Sea Lamprey in Lake Superior: data and code for Bayesian forecast model
<p>Resource managers frequently are tasked with mitigating or reversing adverse effects of invasive species through management policies and actions. In Lake Superior, of the Laurentian Great Lakes, invasive sea lamprey populations are suppressed to protect valuable fish stocks. However, the relationship between choice of long-term control strategy and the future chance of achieving the suppression target is unclear.</p> <p>Using a 60+ year time-series of suppression effort and monitoring data from 50 assessment sites located on Lake Superior tributaries, we developed a Bayesian state-space model to forecast the probability of suppressing lamprey below the suppression target.</p> <p>With annual application of lampricide (i.e., lamprey-specific pesticide) at historical mean levels, we forecasted a 15% chance of achieving the Lake Superior sea lamprey suppression target in 2040.</p> <p>Increasing lampricide effort and/or supplementing lampricide control with age-1 recruitment reduction increased suppression chance. Annual application of the maximum historical lampricide effort resulted in a 50% predicted chance of achieving the target, annual application of the mean historic lampricide effort plus a 40% reduction in recruitment resulted in a 54% chance, and the maximum amount of effort considered (maximum historic lampricide and 60% reduction in recruitment) resulted in a 94% chance.</p> <p><em><a>Policy </a>implications</em>. <a>We</a> developed a simulation model from a robust, long-term monitoring dataset that improves understanding of why long-term sea lamprey suppression objectives have been difficult to achieve in Lake Superior. Furthermore, the model provides a means to gauge efficacy of sea lamprey control policy and action scenarios based on forecasted chance of achieving the suppression target. Creating processes for iteratively refining our forecasting model with stakeholder and technical-expert input and integration with a decision analysis framework could strengthen the link between ecological knowledge obtained from long-term monitoring and invasive sea lamprey management.</p>
Forecasting suppression of invasive Sea Lamprey in Lake Superior: data and code for Bayesian forecast model
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Supplementary material 1 from: Early R, González-Moreno P, Murphy ST, Day R (2018) Forecasting the global extent of invasion of the cereal pest Spodoptera frugiperda, the fall armyworm. NeoBiota 40: 25-50. https://doi.org/10.3897/neobiota.40.28165
Supplementary material : Explanation note: Table S1. Summary of evidence for fall armyworm developmental and population responses to the environment extracted from literature sources. Figure S1. Effect of different sub-sampling proportions and pseudo-absence selection diameters on model predictions (maps). Figure S2. Effect of different sub-sampling proportions and pseudo-absence selection diameters on Balanced Accuracy. Figure S3. Histograms of each environmental variable in 10 arc-minute grid-cells from which the fall armyworm is recorded. Figure S4. Multivariate Environmental Similarity Surface analysis. Figure S5. Empirically measured environmental effects on fall armyworm life cycle. Figure S6. Trade and passenger air transportation within Africa.
Supplementary material 1 from: DeRoy EM, Crookes S, Matheson K, Scott R, McKenzie CH, Alexander ME, Dick JTA, MacIsaac HJ (2022) Predatory ability and abundance forecast the ecological impacts of two aquatic invasive species. NeoBiota 71: 91-112. https://doi.org/10.3897/neobiota.71.75711
Table S1
Supplementary material 2 from: Early R, González-Moreno P, Murphy ST, Day R (2018) Forecasting the global extent of invasion of the cereal pest Spodoptera frugiperda, the fall armyworm. NeoBiota 40: 25-50. https://doi.org/10.3897/neobiota.40.28165
Table S2. Distribution data from the Americas :
ScienceDex guides
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.