Developing a set of key performance indicators for monitoring sustainability of forest functions in the Hyrcanian forests

Abstract

This study identifies key performance indicators for monitoring the sustainability of forest functions in the northern forests of Iran. This process was conducted in two phases through the Delphi method, and Fuzzy Cognitive Mapping (FCM). The Delphi method classified indicators according to two properties, importance and measurability. These were used to identify four classes: (a) important and measurable, (b) important and less measurable, (c) less important and measurable, (d) less important and less measurable. Indicators placed in groups (a) and (b) were then used to develop a set of key performance indicators using FCM. The FCM enabled the evaluation of the overall cumulative impacts of all indicators within the network, individually and collectively, through their interactions with other indicators. The selected methods and possible application of the key performance indicators could be used to determine how to achieve the sustainable management of a forest area.