Céline Genton1, Romane Cristescu2, Sylvain Gatti1, Florence Levréro3, Elodie Bigot1, Peggy Motsch1, Pascaline Le Gouar1, Jean-Sébastien Pierre4, Nelly Ménard1. 1. UMR 6553, ECOBIO-Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Biological Station of Paimpont, Paimpont, France. 2. GeneCology Research Centre, Faculty of Science, Health, Education and Engineering, University of the Sunshine Coast, Sippy Downs, QLD, Australia. 3. Université de Saint-Etienne/Lyon, Equipe de Neuro-Ethologie Sensorielle, Neuro-PSI, CNRS UMR 9197, Saint-Etienne, France. 4. UMR 6553, ECOBIO-Ecosystems, Biodiversity, Evolution, CNRS/University of Rennes 1, Rennes, France.
Abstract
OBJECTIVES: Demographic crashes due to emerging diseases can contribute to population fragmentation and increase extinction risk of small populations. Ebola outbreaks in 2002-2004 are suspected to have caused a decline of more than 80% in some Western lowland gorilla (Gorilla gorilla gorilla) populations. We investigated whether demographic indicators of this event allowed for the detection of spatial fragmentation in gorilla populations. MATERIALS AND METHODS: We collected demographic data from two neighbouring populations: the Lokoué population, suspected to have been affected by an Ebola outbreak (followed from 2001 to 2014), and the Romani population, of unknown demographic status before Ebola outbreaks (followed from 2005 to 2014). RESULTS: Ten years after the outbreak, the Lokoué population is slowly recovering and the short-term demographic indicators of a population crash were no longer detectable. The Lokoué population has not experienced any additional demographic perturbation over the past decade. The Romani population did not show any of the demographic indicators of a population crash over the past decade. Its demographic structure remained similar to that of unaffected populations. DISCUSSION: Our results highlighted that the Ebola disease could contribute to fragmentation of gorilla populations due to the spatially heterogeneous impact of its outbreaks. The demographic structure of populations (i.e., age-sex and group structure) can be useful indicators of a possible occurrence of recent Ebola outbreaks in populations without known history, and may be more broadly used in other emerging disease/species systems. Longitudinal data are critical to our understanding of the impact of emerging diseases on wild populations and their conservation.
OBJECTIVES: Demographic crashes due to emerging diseases can contribute to population fragmentation and increase extinction risk of small populations. Ebola outbreaks in 2002-2004 are suspected to have caused a decline of more than 80% in some Western lowland gorilla (Gorilla gorilla gorilla) populations. We investigated whether demographic indicators of this event allowed for the detection of spatial fragmentation in gorilla populations. MATERIALS AND METHODS: We collected demographic data from two neighbouring populations: the Lokoué population, suspected to have been affected by an Ebola outbreak (followed from 2001 to 2014), and the Romani population, of unknown demographic status before Ebola outbreaks (followed from 2005 to 2014). RESULTS: Ten years after the outbreak, the Lokoué population is slowly recovering and the short-term demographic indicators of a population crash were no longer detectable. The Lokoué population has not experienced any additional demographic perturbation over the past decade. The Romani population did not show any of the demographic indicators of a population crash over the past decade. Its demographic structure remained similar to that of unaffected populations. DISCUSSION: Our results highlighted that the Ebola disease could contribute to fragmentation of gorilla populations due to the spatially heterogeneous impact of its outbreaks. The demographic structure of populations (i.e., age-sex and group structure) can be useful indicators of a possible occurrence of recent Ebola outbreaks in populations without known history, and may be more broadly used in other emerging disease/species systems. Longitudinal data are critical to our understanding of the impact of emerging diseases on wild populations and their conservation.
Authors: Andrew M Robbins; Marie L Manguette; Thomas Breuer; Milou Groenenberg; Richard J Parnell; Claudia Stephan; Emma J Stokes; Martha M Robbins Journal: PLoS One Date: 2022-10-19 Impact factor: 3.752