Javier Bello-Pineda

Modeling α- and β-diversity in a tropical forest from remotely sensed and spatial data

Abstract Comprehensive information on species distribution and species composition patterns of plant communities is required for effective conservation and management of biodiversity. Remote sensing offers an inexpensive means of attaining complete spatial coverage for large areas, at regular time intervals, and can therefore be extremely useful for estimating both species richness and spatial variation of species composition (α- and β-diversity). An essential step to map such attributes is to identify and understand their main drivers. We used remotely sensed data as a surrogate of plant productivity and habitat structure variables for explaining α- and β-diversity, and evaluated the relative roles of productivity-habitat structure and spatial variables in explaining observed patterns of α- and β-diversity by using a Principal Coordinates of Neighbor Matrices analysis. We also examined the relationship between remotely sensed and field data, in order to map α- and β-diversity at the landscape-level in the Yucatan Peninsula, using a regression kriging procedure. These two procedures integrate the relationship of species richness and spatial species turnover both with remotely sensed data and spatial structure. The empirical models so obtained can be used to predict species richness and variation in species composition, and they can be regarded as valuable tools not only for identifying areas with high local species richness (α-diversity), but also areas with high species turnover (β-diversity). Ultimately, information obtained in this way can help maximize the number of species preserved in a landscape.

Dynamics of Fishing Gear and Spatial Allocation of Fishing Effort in a Multispecies Fleet

Abstract Optimization of fishing effort allocation and efficient deployment of fishing gear are necessary for successful management of multispecies fisheries. Campeche Bank, located in the southwestern Gulf of Mexico, provides an opportunity to understand fishing effort and fishing gear dynamics through the analysis of the fishing operations of a semi-industrial fleet and obtain insights into how to identify management units for these types of fisheries. We analyzed the operation of this fleet over 4 years by splitting it into groups and then fully describing the behavior of each one. Our analysis was based on two data sets, including records from logbooks (8,390 fishing trips) and interviews with skippers from fishing vessels at the landing ports (882 trips). We used multivariate statistical techniques (SIMPER, hierarchical cluster analysis, and nonmetric multidimensional scaling analysis) to define targeted species and define the groups (metiers). Geographical information systems tools helped us to iden...

Incorporating expert knowledge for development spatial modeling in assessing ecosystem services provided by coral reefs: A tool for decision-making

Arrecifes coralinos, modelos espaciales, servicios ecosistemicos, conocimiento experto, toma de decisiones Abstract.- Coral reefs provide coastal populations...