30 research outputs found

    Median values of the explanatory variables on different year-scenarios.

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    <p>Circles represent the median values predicted for the available years-scenarios by the hydrodynamic model. Triangles represent the values predicted for the years 2010 and 2100 removing the Delta Works (NDW).</p

    Complete distribution model <i>vs</i> Model of the maxima.

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    <p>Example for <i>C. edule</i>, year 2010. Map produced by sampling from the complete quantile distribution models (A) are able to represent the realistic scatter around (mainly below) the response surface shown in (B). To help the reader in appreciating the fine mosaic of points in (A) we restricted the map to a smaller portion of the basin and we used a logarithmic scale for plotting the estimated values.</p

    Models of the 0.975<i><sup>th</sup></i> quantile, habitat suitability.

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    <p>Once extrapolated to realistic scenarios, the response surface shown in 3 are useful to produce clearly interpretable habitat suitability maps. In the figure we show as example the output for the 1968, 2010 and 2100 scenarios.</p

    Biomass standing stocks, time series.

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    <p>Colored bar show the intertidal (green) and subtidal (blue) realized biomass stock estimated from the different scenarios for the present extension of the basin. Broken-line bars on the years 1968 and 1983 include the area that was cut-off from the beginning of the Oesterdam works in 1979 (25 km<sup>2</sup> between 1968 and 1983 and 12 km<sup>2</sup> between 1983 and 1986). Empty bars on the years 2010 and 2100 show the result of the scenarios simulated removing the Delta Works.</p

    Models validation. Ratio between observed and predicted values.

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    <p>To validate our forecast for each of the modeled quantiles, the whole dataset was sampled with replacement. Due to sampling with replacement, some observations are repeated and others remain unpicked. The model was fitted on the sampled observation (training dataset) and used to predict the unpicked ones (validation dataset). The random sampling-fitting-predicting procedure was iterated 5000 times and repeated for each one of the forecast quantiles. To make predicted (quantiles) and realized values comparable each other, we discretized them in 10 homogeneous classes based on the predicted values. For each of the classes, the correspondent sample quantile of the observed data was calculated. To finally asses the validity of the model, observed and predicted quantiles were plotted against each other and checked for linear correlation. The four quantiles for species showed as examples in the graphs were selected among those predicting occurrence (<i>e.g.</i>, up to the 35<i><sup>th</sup></i> quantile for <i>S. armiger</i>, up to the 78<i><sup>th</sup></i> quantile for <i>L. conchilega</i> <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0089131#pone-0089131-t004" target="_blank">Table 4</a>). The other quantiles generally follow the same trends. The black broken line represent the 1∶1 ratio.</p

    Models of the 0.975<i><sup>th</sup></i> quantile, response surfaces.

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    <p>Models of the maximal biomass, when extrapolated in the explanatory variable space, give a description of the species potential niche consistent with the Liebig's Law.</p
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