Primates are one of many species that are suffering from changes in climate, predation and nutrient flow. Despite global warming being frequently scrutinised in the modern day society, research into the extinction of primates has suggested that time is becoming an ecological constraint (Dunbar, Korstjens and Lehmann 2009). In order to quantify the sustainability of an organism, it is essential to use predictive distribution models as well as the optimum conditions needed by the species.

Primates are a social species that depend on one another for a vast array of essential activities throughout the day. Different species of primate differ in the way of which group sizes are concerned, however research indicates that most primates are being forced to adjust their social behaviour in response to continuous fragmentation of forestry (Korstjens, Dunbar and Lehmann 2010). In light of recent climatic predictions, the effect of increasing temperatures on food sources and group sizes is often analysed. One example of an experiment carried out in the Lacandona Rain Forest, Mexico, involved the observation of spider monkey (Ateles geoffroyi­) populations. The variables tested included forest type (continuous or fragmented) and seasonality (dry or rainy). One of the perceived differences between the monkeys living in continuous forest was that they spent more time feeding and less time travelling than the populations located in the fragmented environment. This may be explained by spatial limitations of the habitat as well as the leafy diet of this particular species (Chaves, Stoner and Arroyo-Rodríguez 2010).

Recent research highlights the importance of sustainability within primate communities. One of the way in which this can be seen is through the group size and individual fitness models. As group size is increased, competition increases with it and so too does individual fitness (Korstjens 2010). The problem however occurs when the group size grows too large and there is too much competition for food. Similar problems occur when the group size is too low because the increase in predation rates. For a species to survive, there needs to be more than one individual in a specific colony. If this is not the case, the population will not be able to breed and will then become extinct (Korstjens 2010).

The Gelada Baboon is a particular species heavily threatened by extinction due to its unique sensitivity to global warming (Dunbar 1998). Research has suggested that should the earth’s temperature increase by seven degrees centigrade, the total population of the species will be forced to relocate to isolated mountain peaks. This is due to the way in which the Baboon’s altitudinal tolerance increases by 500m every two degrees that is increased. In effect, the species would be likely to become extinct due to the lack of resources available in these regions (Dunbar 1998).

Science suggests that climate change could have a prominent effect on the number of primate populations (Dunbar 2009). These predictions have been made due to the ever-increasing amount of evidence surrounding global warming. Temperature increase is projected to diminish vegetation throughout dry regions (particularly Africa) and the rate at which primates are able to evolve may prove vital if they are to avoid extinction.


Dunbar, R.I.M., Korstjens, A. and Lehmann, J., 2009. Time as an ecological constraintBiological Reviews, Volume 84 (3), pp. 413-429.

Available from: [20th March 2012]


Korstjens, A., Dunbar, R.I.M. and Lehmann, J., 2010. Resting time as an ecologicalconstraint on primate biogeography. Animal Behaviour, Volume 79 (2), pp. 361-374, Available from: [20th March 2012]


Chaves, O.M.C, Stoner, K.E.S. and Arroyo-Rodríguez, V.A.R., 2010.

Seasonal Differences in Activity Patterns of Geoffroyi´s Spider Monkeys (Ateles geoffroyi) Living in Continuous and Fragmented Forests in Southern Mexico, Volume 32 (4), pp. 960-973. Available from: [20th March 2012]


Dunbar, R.I.M., 1998. Impact of global warming on the distribution and survival of the gelada baboon: a modelling approach, Volume 4 (3), pp. 293–304.

Available from: [20th March 2012]