Disturbance events strongly influence the dynamics of plant and animal populations within nature reserves. Although many models predict the patterns of succession following a disturbance event, it is often unclear how these models can be used to help make management decisions about disturbances. In this paper we consider the problem of managing fire in Ngarkat Conservation Park (CP), South Australia, Australia. We present a mathematical model of community succession following a fire disturbance event. Ngarkat CP is a key habitat for several nationally rare and threatened species of birds, and because these species prefer different successional communities, we assume that the primary management objective is to maintain community diversity within the park. More specifically, the aim of management is to keep at least a certain fraction of the park, (e.g., 20%), in each of three successional stages. We assume that each year a manager may do one of the following: let wildfires burn unhindered, fight wildfires, or perform controlled burns. We apply stochastic dynamic programming to identify which of these three strategies is optimal, i.e., the one most likely to promote community diversity. Model results indicate that the optimal management strategy depends on the current state of the park, the cost associated with each strategy, and the time frame over which the manager has set his/her goal.

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CrowdRE has been argued to comprise four main activities: motivating crowd members; eliciting feedback; analysing feedback and monitoring context and usage data. However, determining requirements within a software ecosystem poses demands beyond those found by a single product owner. In this paper, we describe open challenges for CrowdRE in handling the many, competing and heterogeneous sources of RE data in a software ecosystem. We illustrate the case of Xero ecosystem-a global accounting software company-as an ecosystem platform provider and Figured-a developer of a farming industry application and one of Xero's partner apps.

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