Limits...
Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

Roux E, Gaborit P, Romaña CA, Girod R, Dessay N, Dusfour I - BMC Ecol. (2013)

Bottom Line: Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors.The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001).The results validate our sampling approach.

View Article: PubMed Central - HTML - PubMed

Affiliation: ESPACE-DEV, UMR228 IRD/UM2/UR/UAG, Institut de Recherche pour le Développement, Maison de la Télédétection, 500 rue Jean-François Breton, 34093 Montpellier Cedex 5, France. emmanuel.roux@ird.fr.

ABSTRACT

Background: Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum.

Results: We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001).

Conclusions: The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Show MeSH

Related in: MedlinePlus

Fuzzy data coding. Example of fuzzy categorization of a real continuous variable. The asterisk indicates that the minimum, median and maximum values are computed on non- values only.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4219608&req=5

Figure 2: Fuzzy data coding. Example of fuzzy categorization of a real continuous variable. The asterisk indicates that the minimum, median and maximum values are computed on non- values only.

Mentions: Variables with a strong positively or negatively skewed distribution were subjected to square-root or square transformations, respectively. Some buffer-based landscape attributes exhibited a “threshold effect”: if the environmental feature of interest was present within the buffer the sites scored non- values with a given distribution but, in some cases, a significant number of sites returned a value as the feature did not exist within the buffer (see Figure2). For such variables, we coded data by computing their membership values with fuzzy intervals, transforming real continuous variables into categorical ones with three categories (or “modalities”)[22-24]. Membership functions are triangular functions, as illustrated in Figure2.


Objective sampling design in a highly heterogeneous landscape - characterizing environmental determinants of malaria vector distribution in French Guiana, in the Amazonian region.

Roux E, Gaborit P, Romaña CA, Girod R, Dessay N, Dusfour I - BMC Ecol. (2013)

Fuzzy data coding. Example of fuzzy categorization of a real continuous variable. The asterisk indicates that the minimum, median and maximum values are computed on non- values only.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4219608&req=5

Figure 2: Fuzzy data coding. Example of fuzzy categorization of a real continuous variable. The asterisk indicates that the minimum, median and maximum values are computed on non- values only.
Mentions: Variables with a strong positively or negatively skewed distribution were subjected to square-root or square transformations, respectively. Some buffer-based landscape attributes exhibited a “threshold effect”: if the environmental feature of interest was present within the buffer the sites scored non- values with a given distribution but, in some cases, a significant number of sites returned a value as the feature did not exist within the buffer (see Figure2). For such variables, we coded data by computing their membership values with fuzzy intervals, transforming real continuous variables into categorical ones with three categories (or “modalities”)[22-24]. Membership functions are triangular functions, as illustrated in Figure2.

Bottom Line: Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors.The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001).The results validate our sampling approach.

View Article: PubMed Central - HTML - PubMed

Affiliation: ESPACE-DEV, UMR228 IRD/UM2/UR/UAG, Institut de Recherche pour le Développement, Maison de la Télédétection, 500 rue Jean-François Breton, 34093 Montpellier Cedex 5, France. emmanuel.roux@ird.fr.

ABSTRACT

Background: Sampling design is a key issue when establishing species inventories and characterizing habitats within highly heterogeneous landscapes. Sampling efforts in such environments may be constrained and many field studies only rely on subjective and/or qualitative approaches to design collection strategy. The region of Cacao, in French Guiana, provides an excellent study site to understand the presence and abundance of Anopheles mosquitoes, their species dynamics and the transmission risk of malaria across various environments. We propose an objective methodology to define a stratified sampling design. Following thorough environmental characterization, a factorial analysis of mixed groups allows the data to be reduced and non-collinear principal components to be identified while balancing the influences of the different environmental factors. Such components defined new variables which could then be used in a robust k-means clustering procedure. Then, we identified five clusters that corresponded to our sampling strata and selected sampling sites in each stratum.

Results: We validated our method by comparing the species overlap of entomological collections from selected sites and the environmental similarities of the same sites. The Morisita index was significantly correlated (Pearson linear correlation) with environmental similarity based on i) the balanced environmental variable groups considered jointly (p = 0.001) and ii) land cover/use (p-value < 0.001). The Jaccard index was significantly correlated with land cover/use-based environmental similarity (p-value = 0.001).

Conclusions: The results validate our sampling approach. Land cover/use maps (based on high spatial resolution satellite images) were shown to be particularly useful when studying the presence, density and diversity of Anopheles mosquitoes at local scales and in very heterogeneous landscapes.

Show MeSH
Related in: MedlinePlus