Two‐Stage Boosted Regression Tree Model to Characterize Southern Flounder Distribution in Texas Estuaries at Varying Population Sizes

Froeschke, John T.; Froeschke, Bridgette F.

doi:10.1080/19425120.2015.1079577

Cited by 21 publications

(5 citation statements)

References 37 publications

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“…Final GAMs were also used to project how lobster distribution may change under two thermally contrasting climatologies (Sagarese et al 2014). Predictive fields were interpolated using ordinary kriging to describe spatial variability in lobster catch density (Froeschke and Froeschke 2016;Tanaka et al 2017). Ordinary kriging procedures were conducted via the automap package (Hiemstra et al 2008) and kriged maps were prepared at 0.03 × 0.03 latitude/longitude grid.…”

Section: Mesoscale Climatic Impacts On Lobster Distributionmentioning

confidence: 99%

Mesoscale climatic impacts on the distribution ofHomarus americanusin the US inshore Gulf of Maine

Tanaka

Chang

Xue

et al. 2019

Can. J. Fish. Aquat. Sci.

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American lobster (Homarus americanus) supports one of the most valuable fisheries in the United States. Spatial distributions of H. americanus are hypothesized to be influenced by climate-driven environmental factors, but such effects have not been quantified. We developed a Tweedie generalized additive model (GAM) to quantify environmental effects on season-, sex-, and size-specific distributions of H. americanus in the inshore Gulf of Maine. Tweedie GAMs were coupled with regional circulation model output to predict spatiotemporal changes in distribution of H. americanus due to mesoscale climate variability. GAM results indicated that bottom temperature and salinity impacts on H. americanus distribution were more pronounced during spring. The coupled climate–niche model predicted significantly higher H. americanus abundance under a warm climatology scenario. This study provides a predictive climate–niche modelling framework that may be useful for planning fishery investments and anticipating management challenges given ongoing climate-driven changes in the Northwest Atlantic.

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Section: Mesoscale Climatic Impacts On Lobster Distributionmentioning

confidence: 99%

Mesoscale climatic impacts on the distribution ofHomarus americanusin the US inshore Gulf of Maine

Tanaka

Chang

Xue

et al. 2019

Can. J. Fish. Aquat. Sci.

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“…The repeated CV predictions in a BRT model is the average taken from many models, thus the models tend to overestimate low values and underestimate high values 53 . To overcome this problem, we explored splitting the data into a presence/absence binomial (Bernoulli) BRT model and a log-transformed presence only Gaussian BRT 53,54 , however the resulting ensemble models performed much poorer than the one-model approach and were therefore abandoned.…”

Section: Discussionmentioning

confidence: 99%

Predicting the spatial abundance of Ixodes ricinus ticks in southern Scandinavia using environmental and climatic data

Kjær

Soleng

Edgar

et al. 2019

Sci Rep

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Recently, focus on tick-borne diseases has increased as ticks and their pathogens have become widespread and represent a health problem in Europe. Understanding the epidemiology of tick-borne infections requires the ability to predict and map tick abundance. We measured Ixodes ricinus abundance at 159 sites in southern Scandinavia from August-September, 2016. We used field data and environmental variables to develop predictive abundance models using machine learning algorithms, and also tested these models on 2017 data. Larva and nymph abundance models had relatively high predictive power (normalized RMSE from 0.65–0.69, R2 from 0.52–0.58) whereas adult tick models performed poorly (normalized RMSE from 0.94–0.96, R2 from 0.04–0.10). Testing the models on 2017 data produced good results with normalized RMSE values from 0.59–1.13 and R2 from 0.18–0.69. The resulting 2016 maps corresponded well with known tick abundance and distribution in Scandinavia. The models were highly influenced by temperature and vegetation, indicating that climate may be an important driver of I. ricinus distribution and abundance in Scandinavia. Despite varying results, the models predicted abundance in 2017 with high accuracy. The models are a first step towards environmentally driven tick abundance models that can assist in determining risk areas and interpreting human incidence data.

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“…The weak regressor algorithm contains two main types, regression tree and support vector machine regression, of which the most commonly used is regression tree [22][23]. The regression tree algorithm flow is shown in Figure 2.…”

Section: Weak Regression Model Selectionmentioning

confidence: 99%

Under the background of ideological and political education, the path optimization of college students’ consumption outlook education based on AdaBoost model

Liu,

Bai

2023

Applied Mathematics and Nonlinear Sciences

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To better help college students establish correct scientific consumption concepts, this paper constructs an analysis model of college students’ consumption views based on the AdaBoost model in augmented learning. Firstly, the consumption data of college students are input into the analysis model and analyzed, and the weights of each sample are initialized. Next, a suitable weak regression model is selected, the corresponding number of iterations is determined, and the current sample weight distribution is updated according to the weak regressor weight coefficients. Using root mean square error adjustment and determining the threshold value, iterative operations are performed. Finally, a strong regression model is derived from analyzing the main factors influencing college students’ consumption perceptions. To verify that the proposed optimization path can help college students establish correct consumption concepts, simulation experiments are designed in this paper. The results show that after relying on peer education to penetrate scientific consumption in the context of Civic Education, some students’ remaining monthly living expenses increased from 300 yuan to 500 yuan. After strengthening self-education to encourage the practice of scientific consumption, the percentage of monthly living expenses stored by male students increased from 5% to 16%. Thus, based on the AdaBoost model, we can derive the factors that affect college students’ consumption to optimize the education path of college students’ consumption concept in a targeted way.

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Two‐Stage Boosted Regression Tree Model to Characterize Southern Flounder Distribution in Texas Estuaries at Varying Population Sizes

Cited by 21 publications

References 37 publications

Mesoscale climatic impacts on the distribution ofHomarus americanusin the US inshore Gulf of Maine

Mesoscale climatic impacts on the distribution ofHomarus americanusin the US inshore Gulf of Maine

Predicting the spatial abundance of Ixodes ricinus ticks in southern Scandinavia using environmental and climatic data

Under the background of ideological and political education, the path optimization of college students’ consumption outlook education based on AdaBoost model

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