Changes between Version 1 and Version 2 of Eda Description

Timestamp:

Feb 1, 2010 10:36:09 PM (15 years ago)

Author:

cedric

Comment:

--

Eda Description

@@ -2 +2 @@
 
 
-Since the early 1980s, the European eel ('' Anguilla anguilla '') stock has been declining and continues to decline at an alarming rate and it’s presently considered outside safe biological limits.
+Since the early 1980s, the European eel ('' Anguilla anguilla '') stock has been declining and continues to decline at an alarming rate. It is presently considered to be outside safe biological limits.
 
-EDA 2.0 (Eel Density Analysis) is a modelling tool using a GIS based approach to predict yellow eel densities. The model is based on a hydrographical database (BD_Carthage® – a spatial referencing system for surface water in France) and (or could be based on two European hydrographical databases: ?) the CCM (Catchment Characterisation and Modelling) River and Catchment Database and the European catchments and Rivers network System (Ecrins). The level of precision of these layers differs; compared to CCM, ECRINS offers a smaller number of elementary catchments.
-This EDA 2.0 model could be/is carried out in three (more?) geographical areas: the Brittany region (Leprévost, 2007), the Loire-Brittany basin (Hoffmann, 2008) and France (Beaulaton in French EMP) (and the Rhône and Vilaine basin cf. mail-POSE model and dataset characterization matrices). The Brittany model allowed to test the obstacles grid from Pierre Steinbach. 
-An analysis with a Generalized Additive Model (GAM) is performed using the electrofishing data set. GAMs, semi-parametric extensions of generalised linear models (GLM) (Hastie and Tibshirani, 1990), are flexible and allow the combination of both linear and complex additive responses within the same model. They are performed using the ‘gam’ library in the R software. The best model is selected by the Akaike’s Information Criterion (AIC).
+EDA 2.0 (Eel Density Analysis) is a modelling tool using a GIS based approach to predict yellow eel densities. The model is based on a hydrographical database (BD_Carthage® – a spatial referencing system for surface water in France) and (or will in its next version be tested on two European hydrographical databases ) the CCM (Catchment Characterisation and Modelling) River and Catchment Database and the European catchments and Rivers network System (Ecrins). The level of precision of these layers differs; compared to CCM, ECRINS offers a smaller number of elementary catchments.[[BR]]
+Within the POSE project, this EDA 2.0 model will be implemented in at least four geographical areas: the Brittany region (Leprévost, 2007), the Loire-Brittany basin (Hoffmann, 2008) , the Rhône and Vaccaress basins, and the  Basque coutry river basins. For management purpose, it will also be implemented across all of France (Beaulaton in French EMP). The implementation of the model in Loire Brittany allowed to predict the effect of river obstacles on densities, and test the obstacles grid from Pierre Steinbach. 
+An analysis with a Generalized Additive Model (GAM) is performed using the electrofishing data set. GAMs, semi-parametric extensions of generalised linear models (GLM) (Hastie and Tibshirani, 1990), are flexible and allow the combination of both linear and complex additive responses within the same model. They are performed using the ‘gam’ library in the R software. The best model is selected by the Akaike’s Information Criterion (AIC), and Kappa when presence-absence models were used.
 
-The presence/absence and density of yellow eel are obtained from the Aquatic environment and fish database (BDMAP - more than 16,000 fishing samples collected on more than 6,000/8,968 (?) sample stations (cf.coordination juillet 2008)) from the National Office of Water and the Aquatic Environments (ONEMA) and other databases from the IAV in the Vilaine watershed and the BGM database in other Brittany watershed.
+The presence/absence and densities of yellow eel are obtained from the Aquatic environment and fish database (BDMAP - more than 16,000 fishing samples collected on more than 6,000/8,968 (?) sampling stations (cf.coordination juillet 2008)) from the National Office of Water and the Aquatic Environments (ONEMA) and other databases from the Brittany watershed.
 Yellow eel densities (YE) are related to different parameters: fishing methods used, environmental conditions (distance to the sea, relative distance, temperature, Strahler stream order, elevation and slope…), anthropogenic conditions (obstacles, fisheries…) and time (year trends).
 
-The distance to the sea, the relative distance (between the distance to the sea and the total length of the river) are calculated from the BDCarthage water network and could be calculated from the CCM and the Ecrins water network.
+The distance to the sea, the relative distance (between the distance to the sea and the total length of the river) are calculated from the BDCarthage water network and from the CCM and the Ecrins water network.
 The temperatures are extracted from the CRU (Climate Research Unit) and Worlclim (www.worldclim.org/). Elevation and slope are extracted from the National Height Elevation Database (BD ALTI® - spatial resolution of 50m) from the National Geographic Institute.
 The obstacle pressure (characteristics, Steinbach rank…) comes from the National list of obstacles to river flows (ROE) from the ONEMA.
@@ -17 +17 @@
 The data sets used to extract the water quality parameters (which ones?) are obtained from the ROM or/and ? the RHP from the ONEMA.
 
-For each point of the French river network (a 2 kilometres segment), the values of those different variables are calculated and allow to predict the yellow eel densities and also the densities in the pristine conditions without anthropogenic impacts (obstacles impacts and fisheries).
-With the water surface, the yellow eel densities are transformed into yellow eel quantities.
-For technical reasons, silver eel densities are unachievable and exhaustive samplings are rare, so an indirect method is used to estimate the silver eel stock from the knowledge of the yellow eel stock. The silver eel stock is obtained with a conversion rate (5%).
+For each point of the French river network (a 2 kilometres segment), the values of those different variables are calculated and allow to predict the yellow eel densities and also the densities in the pristine conditions without anthropogenic impacts (obstacles impacts and fisheries). When multiplied by water surface, the yellow eel densities are transformed into yellow eel absolutes numbers.
+For technical reasons, silver eel densities are unachievable and exhaustive samplings are rare, so an indirect method is used to estimate the silver eel stock from the knowledge of the yellow eel stock. The silver eel stock is obtained with a conversion rate which will be calibrated according to known silver eel productions.