Assumption 1. Meetings among ecologists (e.g., in conferences) are exciting. However, ecologists who want to solve problems in real socioecological contexts must get out of their comfort zone: i.e., the psychological state in which things feel familiar to a researcher, so that they perceive a good control of their environment, experiencing low levels of stress (White, 2009). In a project the disciplinary competence and the social groups concerned are many and heterogeneous: therefore, ecologists should meet engineers, social and agriforest scientists, urban planners, policy makers, administrators and citizens. In this sense, a project-oriented ecologist must be flexible and transversal, be prepared to work in a complex socioecological system, and be prepared to deal with many different points of view. Therefore, a first suggestion for a project-oriented ecologists is open your mind, and free it from prejudices!

Assumption 2. A good ecologist, with a wonderful H index, is not automatically a conservation manager. The in-depth knowledge of ecological targets is not synonymous with technical knowledge of how to search for solutions and make decisions about problems. An ecologist who wants to take action, following a technical–professional approach, should (i) follow a scientific approach (Guthery, 2007) and (ii) become familiar with the problem-solving and PM arenas. Problem solving and PM are not the sum of many disciplines but disciplines themselves. Therefore, be aware of facing a new field of knowledge. The PM arena is transdisciplinary (used in economic–financial, marketing, engineering, social and medical areas) and rich in opportunities that should be exploited by a new generation of applied ecologists.

Assumption 3. The complexity that characterizes the socioecological systems requires a conceptual approach based on system thinking (Cundill et al., 2012). Do not focus only on your targets. The world is much wider! Build causal chains and frameworks modeling the relationships among components (threats vs. targets) using concept and mind maps, causal loops, causal chains, and root-cause analysis (e.g., Margoluis et al., 2009).

Assumption 4. Familiarize yourself with uncertainty. Get ready to make mistakes (do not worry!). The complexity of socioecological systems exposes the projects to uncertainty often leading to forecast errors and surprises (Kay, 2008), which must be managed as opportunities, following an adaptive approach (McCarthy and Possingham, 2007), exploiting its value and gaining experience (“fail fast” approach). There are no unique recipes for success, because targets, conditions and circumstances are unique and their modeling is always incomplete, often with high uncertainty.

Assumption 5. Make clear the sequential logic of a project: context, planning and input (objectives, solutions, decision-making), process, monitoring (outputs, outcomes), adaptive management. A lot of opportunities to grow professionally will be available (Hockings, 2006).

After the assumptions, the following 10 step could complete the framework.

Step 1. Identify the general problem. Conceptualize and put into practice problem solving with a case study, even if simple (for example, in a “km-0 context” you frequent). What is the general problem you would like to solve? What is the criticality (e.g., the threat) that you would like to mitigate? At this stage the problem is identified only generally (no evidence has yet been gathered).

Step 2. Analyze the context and identify the specific problem. The context analysis is used to collect all the information useful to solve it, defining the problem in a more specific way. The better you define the problem, the more likely it is to be solved. Therefore, you should define the targets (their status and criticality), specifying which threats locally impact them (Salafsky et al., 2008).

Step 3. Define an overall project goal and more specific objectives. Name the project and indicate a general purpose. The assignment of a clear and synthetic name is important in communicating the problem to a wider audience. Moreover, you should define pragmatic objectives considering the available resources and the local conditions/circumstances/constraints (environmental, political, social, etc.).

Step 4. Who could solve this problem? What part of the problem can I solve? This is a decisive step to understand if the problem is within the range of skills and resource availability of a few ecologists, or if it is necessary to involve further professionals, stakeholders and citizens. It is rare that a project can be done alone; nevertheless, small groups can do great things. Therefore, activate (or simulate) the establishment of a project team (PT). What part of the problem is solvable and which professional figures can theoretically be involved with the available resources? Following Ashby's law, a problem is much too large compared to available resources in the following cases: (i) the problem is reduced in its complexity or (ii) resources involved to solve it have increased. This is a useful exercise to understand the gap between desirability and feasibility of an environmental change. However, be aware that there are not only the big-money projects. There may be local needs for changing the status of ecological targets even near your place! You can start simulating a pilot project with a real experiment (e.g., through role playing).

Step 5. Know and improve yourself. Analyze the internal context. PM requires a multidisciplinary approach: a project can be articulated involving many different disciplines and sociocultural targets. This requires a constructive and proactive approach; a great openness; and a good attitude to confrontation, listening, curiosity and empathy. Avoid cognitive bias (Kahneman and Lovallo, 1993), epistemic arrogance and nonconstructive behaviors (prejudice, negativity; Battisti, 2018). Since it will always be necessary to work in a team, it will be necessary to spend time through an internal context analysis, identifying strengths and weaknesses of the group and controlling group dynamics. For example, the SWOT analysis (Hill and Westbrook, 1997) is a technique that allows us to analyze strengths and weaknesses of the PT and the opportunities and threats on/against the project. In this regard, a facilitator may be needed. To establish a PT effective over time (therefore resilient, able to recover from a crisis during the project period) it is necessary to increase cognitive diversity (you should avoid building a team with only ecologists), involving both technical–scientific experts and local “wise people” (Intezari and Pauleen, 2018). Different points of view will facilitate the emergence of solutions rather than monodisciplinary groups. Moreover, you should improve the professional redundancy and technical flexibility inside the PT (Shin et al., 2012).

Step 6. Start with creativity to find solutions (even provocative). There are many possible solutions to a problem. The comparison with different world views stimulates creativity, which is useful for finding solutions. Some of these attitudes can be innate; however, creativity techniques (used in the engineering, medical, economic and marketing fields but little used by ecologists) can also be learned (e.g., through brainstorming, brain writing, divergent and lateral thinking; Aslan et al., 2014). Getting a solution (mitigation of a threat, restoring of a new habitat), with the few resources needed and taking into account the constraints, requires an effort of creativity (a term mistakenly assigned only to the artistic field). Thanks to their local expertise, a hydraulic engineer can provide a solution to the creation of a new habitat for a rare wetland bird or a fish farmer (belonging to the wise people) who knows the site history can suggest a solution for river restoration, since it know seasonality of local human activities, and so on.

Step 7. Decide between various options. Of the many solutions only one or a few will be selected (decision-making process; convergent thinking; Basadur and Hausdorf, 1996). Cost–benefit analysis, risk analysis and multicriteria approaches carried out for each option can direct the decision makers (Battisti, 2018).

Step 8. Plan the actions and the start process. Once the most suitable option has been chosen, actions must be defined to obtain the results. Schedule times, roles and responsibilities, and resources committed (budget, operators, materials, technology), and, finally, start with the operational phase. Efficiency must be guaranteed to meet deadlines and the methods indicated in the planning. Be careful with time thieves, and do not procrastinate!

Step 9. Did we carry out the planned works, activities and products (first-level results: outputs)? Did we get the expected results on our environmental targets (second-level results: outcomes)? The results in terms of actions represent the first level of monitoring. The results in terms of effects on targets represent the second level of monitoring (McDonald-Madden et al., 2011). The indicators necessary to verify the effectiveness of the project at this level will have been chosen in advance. The arsenal of PM is rich in suggestions for carrying out opportune sampling designs and a logic to select appropriate indicators: see the BACI (before–after control–impact) design that allows a monitoring focused on the effect before and after a threat or project compared to control sites (Bro et al., 2004) and the DPSIR (driving forces–pressure–state–impact–response) that is useful to select indicators for different processes and factors (Kimmel et al., 2010).

Step 10. What did not go as planned? How can I improve? Have I communicated successes (or failures)? In complex socioecological systems, many expected results will not be achieved due to errors in design scenarios or during the operational actions. In this sense the only predictable thing about a project is that errors will be made. The project should be itself monitored through an adaptive approach (Margoluis et al., 2009).

Finally, all projects should end with the same communication actions. Successes (and failures) must be communicated in different ways (social media, publications) to make the experience and lessons learned shared.

No data sets were used in this article.

All authors contributed critically to the drafts and gave final approval for publication.

The authors declare that they have no conflict of interest.

This paper was edited by Daniel Montesinos and reviewed by Maria Amélia Martins-Loução.