Modelling landscape connectivity change for chimpanzee conservation in Tanzania
Chimpanzees, like all great ape species, have experienced a dramatic decline in global numbers during the past decades. The degradation, fragmentation and loss of suitable habitat impede chimpanzee movements, reducing the potential for dispersal and thus population viability. In Tanzania, 90% of the...
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Veröffentlicht in: | Biological conservation 2020-12, Vol.252, p.108816, Article 108816 |
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Sprache: | eng |
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Zusammenfassung: | Chimpanzees, like all great ape species, have experienced a dramatic decline in global numbers during the past decades. The degradation, fragmentation and loss of suitable habitat impede chimpanzee movements, reducing the potential for dispersal and thus population viability. In Tanzania, 90% of the 2000–3000 remaining chimpanzees are found within the Greater Mahale Ecosystem (GME), the majority of which live at low densities outside of national park boundaries. Recent genetic analyses have identified potential boundaries between the northern and southern populations of the GME. Using landscape connectivity modelling, we aimed to clarify population connectivity across this vast ecosystem (>20,000 km2) and assess change over time. We developed habitat suitability models to create an index of habitat selection by chimpanzees and mapped connectivity using circuit theory. Our results suggest that, in recent history (1973), the entire ecosystem was linked by a series of corridors showing a high likelihood of chimpanzee movement. Our analysis also reveals a reduction of connectivity by 2017 impacting the two corridors linking the northern and southern GME. When projected to 2027, areas contributing to connectivity are predicted to continue to decline, threatening all available corridors between the northern and southern GME. By modelling connectivity across time, we were able to identify key areas to focus conservation efforts to maintain population viability within the largest chimpanzee population in Tanzania. |
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ISSN: | 0006-3207 1873-2917 |
DOI: | 10.1016/j.biocon.2020.108816 |