Using Genetic Profiles of African Forest Elephants to Infer Population Structure, Movements, and Habitat Use in a Conservation and Development Landscape in Gabon

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Conservation of wide-ranging species, such as the African forest elephant (Loxodonta cyclotis), depends on fully protected areas and multiple-use areas (MUA) that provide habitat connectivity. In the Gamba Complex of Protected Areas in Gabon, which includes 2 national parks separated by a MUA containing energy and forestry concessions, we studied forest elephants to evaluate the importance of the MUA to wide-ranging species. We extracted DNA from elephant dung samples and used genetic information to identify over 500 individuals in the MUA and the parks. We then examined patterns of nuclear microsatellites and mitochondrial control-region sequences to infer population structure, movement patterns, and habitat use by age and sex. Population structure was weak but significant, and differentiation was more pronounced during the wet season. Within the MUA, males were more strongly associated with open habitats, such as wetlands and savannas, than females during the dry season. Many of the movements detected within and between seasons involved the wetlands and bordering lagoons. Our results suggest that the MUA provides year-round habitat for some elephants and additional habitat for others whose primary range is in the parks. With the continuing loss of roadless wilderness areas in Central Africa, well-managed MUAs will likely be important to the conservation of wide-ranging species.

Related collections

Most cited references 23

Record: found
Abstract: found
Article: not found

Estimating the probability of identity among genotypes in natural populations: cautions and guidelines.

L P Waits, G Luikart, P Taberlet (2001)

Individual identification using DNA fingerprinting methods is emerging as a critical tool in conservation genetics and molecular ecology. Statistical methods that estimate the probability of sampling identical genotypes using theoretical equations generally assume random associations between alleles within and among loci. These calculations are probably inaccurate for many animal and plant populations due to population substructure. We evaluated the accuracy of a probability of identity (P(ID)) estimation by comparing the observed and expected P(ID), using large nuclear DNA microsatellite data sets from three endangered species: the grey wolf (Canis lupus), the brown bear (Ursus arctos), and the Australian northern hairy-nosed wombat (Lasiorinyus krefftii). The theoretical estimates of P(ID) were consistently lower than the observed P(ID), and can differ by as much as three orders of magnitude. To help researchers and managers avoid potential problems associated with this bias, we introduce an equation for P(ID) between sibs. This equation provides an estimator that can be used as a conservative upper bound for the probability of observing identical multilocus genotypes between two individuals sampled from a population. We suggest computing the actual observed P(ID) when possible and give general guidelines for the number of codominant and dominant marker loci required to achieve a reasonably low P(ID) (e.g. 0.01-0.0001).

0 comments Cited 456 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: not found
Article: not found

Global Percent Tree Cover at a Spatial Resolution of 500 Meters: First Results of the MODIS Vegetation Continuous Fields Algorithm

M. Hansen, R DeFries, J. R. G. Townshend … (2003)

0 comments Cited 262 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Quantifying the lag time to detect barriers in landscape genetics.

E Landguth, S A Cushman, M Schwartz … (2010)

Understanding how spatial genetic patterns respond to landscape change is crucial for advancing the emerging field of landscape genetics. We quantified the number of generations for new landscape barrier signatures to become detectable and for old signatures to disappear after barrier removal. We used spatially explicit, individual-based simulations to examine the ability of an individual-based statistic [Mantel's r using the proportion of shared alleles' statistic (Dps)] and population-based statistic (FST ) to detect barriers. We simulated a range of movement strategies including nearest neighbour dispersal, long-distance dispersal and panmixia. The lag time for the signal of a new barrier to become established is short using Mantel's r (1-15 generations). FST required approximately 200 generations to reach 50% of its equilibrium maximum, although G'ST performed much like Mantel's r. In strong contrast, FST and Mantel's r perform similarly following the removal of a barrier formerly dividing a population. Also, given neighbour mating and very short-distance dispersal strategies, historical discontinuities from more than 100 generations ago might still be detectable with either method. This suggests that historical events and landscapes could have long-term effects that confound inferences about the impacts of current landscape features on gene flow for species with very little long-distance dispersal. Nonetheless, populations of organisms with relatively large dispersal distances will lose the signal of a former barrier within less than 15 generations, suggesting that individual-based landscape genetic approaches can improve our ability to measure effects of existing landscape features on genetic structure and connectivity. © 2010 Blackwell Publishing Ltd.