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  • Print publication year: 2018
  • Online publication date: July 2018

7 - Predicting Mule Deer Harvests in Real Time


Ungulates are an important group of species across the world that have strong ecological impacts on terrestrial vegetation and food-webs, as well as being economically valued for recreational hunting, bushmeat, and impacts on agriculture. Consequently, it would be useful to predict their population dynamics ahead of time for many management and conservation applications, yet there are almost no cases of prediction being used to guide management of these key species. In the case of recreational harvest, wildlife managers across the world are often faced with setting harvest quotas of ungulates one or two years before harvest implementation. These lags between determining the harvest quotas and the actual harvest period can often induce undesirable population oscillations of game species. This can also have consequences for other aspects of the ecosystem, including threatened or declining species. Here, we illustrate a predictive harvest management model applied to improving the harvest of mule deer, an economically and ecologically important ungulate across the state of Idaho, USA. Previously developed predictive models of key population parameters such as overwinter fawn survival were developed that linked to remotely sensed measures of vegetation productivity and snow cover from the MODIS platform. Models of these demographic rates were then included in an integrated population model that could forecast overwinter survival in late autumn when hunting seasons are set in Idaho. These models enabled managers to adjust their harvest quotas for the subsequent autumn based on readily available remotely sensed data in real-time. We demonstrate the improvements to harvest management of mule deer by comparing what harvests would have been with and without remotely sensed data. We also provide lessons for the necessary management and operational conditions that needed to be present in the Idaho Department of Fish and Game to enable such a successful, centralised, prediction system with recommendations for other management and conservation agencies. In conclusion, remote sensing measures of terrestrial environmental conditions can be a powerful tool to improve the management of ungulates worldwide.

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