Not Seeing the Wood for the Trees

Rogers, Alex D.; Sack, Karen

doi:10.1111/1758-5899.12001

Cited by 3 publications

(3 citation statements)

References 15 publications

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“…Amendments to existing legislation could also be introduced to make enforcement possible and straightforward. For example, the International Maritime Organization's International Convention for the Safety of Life at Sea (SOLAS) could be amended so that the mandatory requirement for shipping vessels to carry and actively use an Automatic Identification System (AIS) and to have a mandatory and permanent vessel identification number could also be applied to fishing vessels 25 . These potential options and other questions regarding the logistics of closing the high seas to fishing remain to be explored fully, but the satellite technology for surveillance exists and is currently used by the shipping industry.…”

Section: Discussionmentioning

confidence: 99%

Winners and losers in a world where the high seas is closed to fishing

Sumaila

Lam

Miller

et al. 2015

Sci Rep

143

112

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Fishing takes place in the high seas and Exclusive Economic Zones (EEZs) of maritime countries. Closing the former to fishing has recently been proposed in the literature and is currently an issue of debate in various international fora. We determine the degree of overlap between fish caught in these two areas of the ocean, examine how global catch might change if catches of straddling species or taxon groups increase within EEZs as a result of protection of adjacent high seas; and identify countries that are likely to gain or lose in total catch quantity and value following high-seas closure. We find that <0.01% of the quantity and value of commercial fish taxa are obtained from catch taken exclusively in the high seas, and if the catch of straddling taxa increases by 18% on average following closure because of spillover, there would be no loss in global catch. The Gini coefficient, which measures income inequality, would decrease from 0.66 to 0.33. Thus, closing the high seas could be catch-neutral while inequality in the distribution of fisheries benefits among the world's maritime countries could be reduced by 50%.

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Section: Discussionmentioning

confidence: 99%

Winners and losers in a world where the high seas is closed to fishing

Sumaila

Lam

Miller

et al. 2015

Sci Rep

143

112

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“…The environmental data included in the analysis as predictor variables are 1 km 2 resolution satellite images and meteorological data in raster file format, commonly used for mosquito distribution modelling [ 30 ]. The images were obtained from the MODIS sensor on NASA’s Terra and Aqua satellites [ 31 , 32 ] for 2000–2012 and subjected to temporal Fourier transformation [ 33 , 34 ] to summarise the images and to produce sets of data that capture characteristics of the annual seasonality: the mean, the annual bi-annual and tri-annual amplitudes and phases, the maxima, minima and variances of variances of the middle infra-red (MIR), the daytime Land Surface Temperature (dLST), the night-time Land Surface Temperature (nLST), the Enhanced Vegetation Index (EVI) and the Normalized Difference Vegetation Index (NDVI) signals [ 35 ]. Other environmental data used in this study are precipitation (WorldClim [ 36 ] and CMORPH [ 37 ] 1950–2000), population density (compiled from the Gridded Population of the World Dataset 2000 [ 38 ]), the digital elevation model (MODIS [ 32 ] 2012) and land cover (Corine land cover map of 2006) [ 39 ].…”

Section: Methodsmentioning

confidence: 99%

Modelling the potential spatial distribution of mosquito species using three different techniques

2015

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BackgroundModels for the spatial distribution of vector species are important tools in the assessment of the risk of establishment and subsequent spread of vector-borne diseases. The aims of this study are to define the environmental conditions suitable for several mosquito species through species distribution modelling techniques, and to compare the results produced with the different techniques.MethodsThree different modelling techniques, i.e., non-linear discriminant analysis, random forest and generalised linear model, were used to investigate the environmental suitability in the Netherlands for three indigenous mosquito species (Culiseta annulata, Anopheles claviger and Ochlerotatus punctor). Results obtained with the three statistical models were compared with regard to: (i) environmental suitability maps, (ii) environmental variables associated with occurrence, (iii) model evaluation.ResultsThe models indicated that precipitation, temperature and population density were associated with the occurrence of Cs. annulata and An. claviger, whereas land surface temperature and vegetation indices were associated with the presence of Oc. punctor. The maps produced with the three different modelling techniques showed consistent spatial patterns for each species, but differences in the ranges of the predictions. Non-linear discriminant analysis had lower predictions than other methods. The model with the best classification skills for all the species was the random forest model, with specificity values ranging from 0.89 to 0.91, and sensitivity values ranging from 0.64 to 0.95.ConclusionsWe mapped the environmental suitability for three mosquito species with three different modelling techniques. For each species, the maps showed consistent spatial patterns, but the level of predicted environmental suitability differed; NLDA gave lower predicted probabilities of presence than the other two methods. The variables selected as important in the models were in agreement with the existing knowledge about these species. All model predictions had a satisfactory to excellent accuracy; best accuracy was obtained with random forest. The insights obtained can be used to gain more knowledge on vector and non-vector mosquito species. The output of this type of distribution modelling methods can, for example, be used as input for epidemiological models of vector-borne diseases.

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“…The environmental data included in the analysis as predictor variables are 1 km 2 resolution satellite images and meteorological data in raster file format, commonly used for mosquito distribution modelling [ 21 ]. The images were obtained from the MODIS sensor on NASA’s Terra and Aqua satellites [ 22 , 23 ] for 2000–2012 and subjected to temporal Fourier transformation [ 24 , 25 ] to summarise the images and to produce sets of data that capture characteristics of the annual seasonality: the mean, the annual, bi-annual and tri-annual amplitudes and phases, the maxima, minima and variances of the middle infra-red, day and night-time land surface temperature, the enhanced vegetation index and the normalized difference vegetation index signals [ 26 ]. Other environmental data used in this study are precipitation (WorldClim [ 27 ] and CMORPH [ 28 ] 1950–2000), population density (compiled from the Gridded Population of the World Dataset 2000 [ 29 ]), the digital elevation model (MODIS [ 23 ] 2012) and land cover (Corine land cover map of 2006 [ 30 ]).…”

Section: Methodsmentioning

confidence: 99%

Modelling the spatial distribution of the nuisance mosquito species Anopheles plumbeus (Diptera: Culicidae) in the Netherlands

Ibáñez-Justicia

Cianci

2015

Parasites Vectors

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BackgroundLandscape modifications, urbanization or changes of use of rural-agricultural areas can create more favourable conditions for certain mosquito species and therefore indirectly cause nuisance problems for humans. This could potentially result in mosquito-borne disease outbreaks when the nuisance is caused by mosquito species that can transmit pathogens. Anopheles plumbeus is a nuisance mosquito species and a potential malaria vector. It is one of the most frequently observed species in the Netherlands. Information on the distribution of this species is essential for risk assessments. The purpose of the study was to investigate the potential spatial distribution of An. plumbeus in the Netherlands.MethodsRandom forest models were used to link the occurrence and the abundance of An. plumbeus with environmental features and to produce distribution maps in the Netherlands. Mosquito data were collected using a cross-sectional study design in the Netherlands, from April to October 2010–2013. The environmental data were obtained from satellite imagery and weather stations. Statistical measures (accuracy for the occurrence model and mean squared error for the abundance model) were used to evaluate the models performance. The models were externally validated.ResultsThe maps show that forested areas (centre of the Netherlands) and the east of the country were predicted as suitable for An. plumbeus. In particular high suitability and high abundance was predicted in the south-eastern provinces Limburg and North Brabant. Elevation, precipitation, day and night temperature and vegetation indices were important predictors for calculating the probability of occurrence for An. plumbeus. The probability of occurrence, vegetation indices and precipitation were important for predicting its abundance. The AUC value was 0.73 and the error in the validation was 0.29; the mean squared error value was 0.12.ConclusionsThe areas identified by the model as suitable and with high abundance of An. plumbeus, are consistent with the areas from which nuisance was reported. Our results can be helpful in the assessment of vector-borne disease risk.

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Not Seeing the Wood for the Trees

Cited by 3 publications

References 15 publications

Winners and losers in a world where the high seas is closed to fishing

Winners and losers in a world where the high seas is closed to fishing

Modelling the potential spatial distribution of mosquito species using three different techniques

Modelling the spatial distribution of the nuisance mosquito species Anopheles plumbeus (Diptera: Culicidae) in the Netherlands

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