Cork oak (Quercus suber L.) and holm oak (Quercus rotundifolia) ecosystems are characteristic of Mediterranean forestry in Portugal. Even though cork is the most valuable product, these ecosystems provide multiple products and services. Assessing trade-offs between multiple goals is thus critical for the effectiveness of oak ecosystem management planning. This paper focuses on the development of a decision support system for oak ecosystems’ scenario analysis including multiple criteria. It includes an innovative decision support systems (DSS) functionality to assess trade-offs between the criteria that may support negotiation and consensus building between decision-makers and forest stakeholders. Specifically, a module that encapsulates the Feasible Goals Method/Interactive Decision Maps (FGM/IDM) technique is developed for interactive visualization of the Pareto frontier. The Pareto frontier illustrates the degree to which improving one particular criterion requires accepting sacrifices in the achievements of others. It thus provides information about trade-offs between competing decision-makers’ preferences. Results are discussed for a large-scale application encompassing over 1 million ha of cork and holm oak forest ecosystems in Southern Portugal. This study demonstrates the potential of the new DSS functionality to enhance multi-objective forest planning, namely by facilitating participation by stakeholders and providing transparency to the decision-making processes.

Long-term vegetation monitoring projects are often used to evaluate how plant communities change through time in response to some external influence. Here, we evaluate the efficacy of vegetation monitoring to consistently detect changes in white-tailed deer browsing effects. Specifically, we compared inter-rater reliability (Cohen’s κ and Lin’s concordance correlation coefficient) between two identically trained field crews for several plant metrics used by Pennsylvania state agencies to monitor deer browsing impact. Additionally, we conducted a power analysis to determine the effect of sampling scale (1/2500th or 1/750th ha plots) on the ability to detect changes in tree seedling stem counts over time. Inter-rater reliability across sampling crews was substantial for most metrics based on direct measurements, while the observational based Deer Impact Index (DII) had only moderate inter-rater reliability. The smaller, 1/2500th ha sampling scale resulted in higher statistical power to detect changes in tree seedling stem counts due to reduced observer error. Overall, this study indicates that extensive training on plant identification, project protocols, and consistent data collection methods can result in reliable vegetation metrics useful for tracking understory responses to white-tailed deer browsing. Smaller sampling scales and objective plant measures (i.e., seedling counts, species richness) improve inter-rater reliability over subjective measures of deer impact (i.e., DII). However, considering objective plant measures when making a subjective assessment regarding deer browsing effects may also improve DII inter-rater reliability.