Spatio-temporal patterns in the distribution of the multi-mammate mouse, Mastomys natalensis, in rice crop and fallow land habitats in Tanzania

  • Mulungu L
  • Sixbert V
  • Ngowo V
 et al. 
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An understanding of the dispersion patterns of a pest is an important pre-requisite for developing an effective management programme for the pest. In this study, rodents were trapped in two rice fields and two fallow fields for three consecutive nights each month from June 2010 to May 2012. Mastomys natalensis was the most abundant rodent pest species in the study area, accounting for >95% of the trapped rodent community. Rattus rattus, Dasymys incomtus, Acomys spinosissimus and Grammomys dolichurus comprised relatively small proportions of the trapped population. Morisita's index of dispersion was used to measure the relative dispersal pattern (aggregate, random, uniform) of individuals across each trapping grid as a means of comparing rodent distribution in rice and fallow fields over time. This analysis revealed that the rodents in rice fields generally exhibited an aggregated spatio-temporal distribution. However, the rodents in fallow fields were generally less aggregated, approaching a random distribution in some habitats and seasons. Heat maps of trapping grids visually confirmed these dispersal patterns, indicating the clumped or random nature of captured rodents. ANOVA showed that the parameters of habitat (rice, fallow), crop stage (transplanting, vegetative, booting, maturity) and cropping season (wet, dry) all significantly impacted the number of rodents captured, with the vegetative, dry season, fallow habitat having the highest number of rodents; and the transplanting, wet season, rice habitat with the least number of rodents. Therefore, such spatio-temporal patterns can serve as a tool for developing stratified biodiversity sampling plans for small mammals and decision making for rodent pest management strategies.

Author-supplied keywords

  • aggregate distribution
  • dispersion
  • irrigated rice
  • pest management
  • small mammals

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