Using social media to measure the contribution of red list species to the nature-based tourism potential of African protected areas

TY - JOUR

T1 - Using social media to measure the contribution of red list species to the nature-based tourism potential of African protected areas

AU - Willemen, Louise

AU - Cottam, Andrew J.

AU - Drakou, Evangelia G.

AU - Burgess, Neil David

PY - 2015

Y1 - 2015

N2 - Cultural ecosystem services are defined by people's perception of the environment, which make them hard to quantify systematically. Methods to describe cultural benefits from ecosystems typically include resource-demanding survey techniques, which are not suitable to assess cultural ecosystem services for large areas. In this paper we explore a method to quantify cultural benefits through the enjoyment of natured-based tourism, by assessing the potential tourism attractiveness of species for each protected area in Africa using the IUCN's Red List of Threatened Species. We use the number of pictures of wildlife posted on a photo sharing website as a proxy for charisma, popularity, and ease of observation, as these factors combined are assumed to determine how attractive species are for the global wildlife tourist. Based on photo counts of 2473 African animals and plants, species that seem most attractive to nature-based tourism are the Lion, African Elephant and Leopard. Combining the photo counts with species range data, African protected areas with the highest potential to attract wildlife tourists based on attractive species occurrence were Samburu National Reserve in Kenya, Mukogodo Forest Reserve located just north of Mount Kenya, and Addo Elephant National Park in South-Africa. The proposed method requires only three data sources which are freely accessible and available online, which could make the proposed index tractable for large scale quantitative ecosystem service assessments. The index directly links species presence to the tourism potential of protected areas, making the connection between nature and human benefits explicit, but excludes other important contributing factors for tourism, such as accessibility and safety. This social media based index provides a broad understanding of those species that are popular globally; in many cases these are not the species of highest conservation concern.

AB - Cultural ecosystem services are defined by people's perception of the environment, which make them hard to quantify systematically. Methods to describe cultural benefits from ecosystems typically include resource-demanding survey techniques, which are not suitable to assess cultural ecosystem services for large areas. In this paper we explore a method to quantify cultural benefits through the enjoyment of natured-based tourism, by assessing the potential tourism attractiveness of species for each protected area in Africa using the IUCN's Red List of Threatened Species. We use the number of pictures of wildlife posted on a photo sharing website as a proxy for charisma, popularity, and ease of observation, as these factors combined are assumed to determine how attractive species are for the global wildlife tourist. Based on photo counts of 2473 African animals and plants, species that seem most attractive to nature-based tourism are the Lion, African Elephant and Leopard. Combining the photo counts with species range data, African protected areas with the highest potential to attract wildlife tourists based on attractive species occurrence were Samburu National Reserve in Kenya, Mukogodo Forest Reserve located just north of Mount Kenya, and Addo Elephant National Park in South-Africa. The proposed method requires only three data sources which are freely accessible and available online, which could make the proposed index tractable for large scale quantitative ecosystem service assessments. The index directly links species presence to the tourism potential of protected areas, making the connection between nature and human benefits explicit, but excludes other important contributing factors for tourism, such as accessibility and safety. This social media based index provides a broad understanding of those species that are popular globally; in many cases these are not the species of highest conservation concern.

U2 - 10.1371/journal.pone.0129785

DO - 10.1371/journal.pone.0129785

M3 - Journal article

C2 - 26068111

AN - SCOPUS:84935511904

SN - 1932-6203

VL - 10

JO - PLoS Computational Biology

JF - PLoS Computational Biology

IS - 6

M1 - e0129785

ER -