Maria Adelia Widijanto

(University of Copenhagen)

The Virtual Laboratory

Uncertainties have always been the fundamental enemy of human nature. To face this, models serve as a “virtual laboratory” where problems are translated into mathematical forms to predict possible outcomes. In forestry, reducing future uncertainty through forest modeling has widened its scope over time. Starting with the use to estimate yield production and management purposes, forest models now also serve to predict how forests will change under climate change. Forest modeling helps to understand complex forest ecosystems, predict the impacts of environmental changes, and inform policy decisions to effectively manage forests. 

While basic ecological knowledge has been well-established for decades, advances in forest modeling have primarily resulted from technological innovations rather than new ecological discoveries. Technologies such as earth observation and artificial intelligence have improved the process by providing real-time data and simplifying the understanding of interconnected ecosystem patterns. These innovations have enhanced model accuracy and efficiency, uncovering new insights into forest behaviors.

As today’s world faces increasing uncertainties, the role of forest modeling experts is becoming more recognized. However, despite this growing acknowledgment, establishing a professional career path is still challenging for a forestry student.

Educational Challenges

While it is true that learning is a never-ending process, the learning curve is particularly steep for young researchers to enter this field. Educational institutions face significant challenges in integrating various subjects into a cohesive syllabus. Forest science is inherently interdisciplinary, ranging from soil chemistry, hydrology, to organizational management. While on one side this made the graduates more versatile, by the end of the program, it is often hard for the student to integrate all the information gathered over the program. 

The era of information technology advancements has led to the introduction of computer and data science into academic programs, starting as early as the bachelor’s degree. While integrating new subjects like data science and remote sensing can enhance the curriculum, it also risks making the degree overly complex and potentially end up being just bells and whistles to the program. The challenge lies in identifying which subjects are essential that are relevant to the current job demand, given the limited timeframe of study time. 

The competition for career opportunities is fierce, and most forestry graduates are at a disadvantage with graduates from other “practical” sectors, such as geoinformatician or computer scientists. Open-access learning resources and intensive bootcamp programs are commonly used by forestry students as a supplement to their degrees and additional “assets” to jumpstart their careers. However, this emphasizes how forestry graduates have relatively low advantages in this field of expertise with their degree alone.

The challenge is further compounded by the lack of resources to teach in these developing disciplines. Emerging niche fields like forest modeling often lack a dedicated faculty, with courses being taught by experts from adjacent disciplines. Often, institutions must rely on experts from other related disciplines to provide “introductory” courses, which may not offer the depth of knowledge required for true specialization.

It’s Not Only Technical Problems

One of the main goals of producing model projections is to inform the policymakers. Effective science communication strategies, such as visualizations and simplified summaries, are essential for translating complex model results into comprehensible policy recommendations. 

Therefore, there is also a demand for forest modelers to understand the socio-economic and political situation to be able to communicate their findings efficiently. While they possess the technical expertise to create sophisticated models, translating their findings into clear and concise messages for policymakers and the public is often challenging. This communication barrier can hinder the practical application of valuable research and eventually limit the impact of forest modeling on policy decisions.

Creating More Opportunities

With this high expectation of forest modelers, the challenge relies on designing education systems that equip students properly. Yet, it is crucial to strike a balance to ensure that students don’t end up being jacks of all trades but masters of none. By this, young scientists can also be involved in the research contributions. 

Supporting young researchers in starting a career in forest modeling is essential for creating a resilient generation of scientists who can contribute to building resilient forests for the future. Reforming the education system to adjust the job demand is necessary, making the career’s entry point accessible not only as a “career shift” for senior scientists but as a dedicated career path for newcomers. Beyond this, creating equal opportunities for people from less advantaged groups is also crucial. Investing in the careers of young researchers is investing in our forests for future generations.

References

Blanco, J. A., & Lo, Y. H. (2023). Latest trends in modelling forest ecosystems: new approaches or just new methods?. Current Forestry Reports, 9(4), 219-229.

DeAngelis, D. L., Franco, D., Hastings, A., Hilker, F. M., Lenhart, S., Lutscher, F., … & Tyson, R. C. (2021). Towards building a sustainable future: positioning ecological modelling for impact in ecosystems management. Bulletin of Mathematical Biology, 83, 1-28.

Innes, J. L. (2005). Multidisciplinarity, interdisciplinarity and training in forestry and forest research. The forestry chronicle, 81(3), 324-329.