Factors affecting species richness of marine elasmobranchs

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• 作者：Cástor Guisande (1)
  Bernardo Patti (2)
  Antonio Vaamonde (3)
  Ana Manjarrés-Hernández (4)
  Patricia Pelayo-Villamil (5)
  Emilio García-Roselló (6)
  Jacinto González-Dacosta (6)
  Jürgen Heine (6)
  Carlos Granado-Lorencio (7)
  
• 关键词：Sharks ; Batoids ; Species richness ; Area of occupancy
• 刊名：Biodiversity and Conservation
• 出版年：2013
• 出版时间：July 2013
• 年：2013
• 卷：22
• 期：8
• 页码：1703-1714
• 全文大小：555KB
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• 作者单位：Cástor Guisande (1)
  Bernardo Patti (2)
  Antonio Vaamonde (3)
  Ana Manjarrés-Hernández (4)
  Patricia Pelayo-Villamil (5)
  Emilio García-Roselló (6)
  Jacinto González-Dacosta (6)
  Jürgen Heine (6)
  Carlos Granado-Lorencio (7)
  
  1. Facultad de Ciencias, Universidad de Vigo, Lagoas-Marcosende, 36200, Vigo, Spain
  2. Istituto per l’Ambiente Marino Costiero, U.O. Capo Granitola, Consiglio Nazionale delle Ricerche, Via del Mare 3, Campobello di Mazara, TP, 91021, Italy
  3. Departamento de Estadística e Investigación Operativa Facultad de CCEE y Empresariales, Universidad de Vigo, Torrecedeira 105, 36208, Vigo, Spain
  4. Instituto Amazónico de Investigaciones-IMANI, Universidad Nacional de Colombia, A.A. 215, Leticia, Colombia
  5. Grupo de Ictiología, Universidad de Antioquia, Medellín, A.A. 1226, Colombia
  6. Departamento de Informática, Edificio Fundición, Universidad de Vigo, Campus Lagoas-Marcosende, 36310, Vigo, Spain
  7. Departamento de Biología Vegetal y Ecología Facultad de Biología, Universidad de Sevilla, Sevilla, Spain
  

文摘

Many studies on elasmobranchs, sharks and batoids (rays, skates and guitarfishes), have focused on the factors responsible for biomass decline, but little attention has been paid to the factors that affect species richness. We used the software package ModestR to determine the geographical distribution of all valid marine elasmobranch species (512 species of sharks and 619 species of batoids), thereby making it possible to determine the species composition of the elasmobranch community in any area worldwide. The primary aim of this study was to identify the factors associated with the species richness of elasmobranchs. The data were analyzed using multiple regressions and Support Vector Machine (SVM) in cells of 1o×?1o with the analyzed abiotic variables being bathymetry, chlorophyll a, sea surface temperature, photosynthetically available radiation, pH, cloud cover, the concentrations of calcite, silicate, phosphate and nitrate, salinity, particulate organic carbon, diffuse attenuation and dissolved oxygen. The mean area of occupancy of the species was used as an indicator of niche occupancy. The model performed with SVM explained 97 and 99?% of the variance observed in the species richness of batoids and sharks, respectively. Mean area of occupancy, temperature and bathymetry were the variables with a higher contribution to the variance observed in both sharks and batoids. The negative residuals of the model performed with SVM indicated areas with lower than predicted species richness. These may be potential areas with undiscovered and/or unregistered species, or areas with decreased species richness due to the negative effect of anthropogenic factors, i.e. overfishing