The Future of Forests: Forecasting and Managing for Change | 9am PT, Tues July 15, 2024

[Grigory Bronevetsky]

Modeling Talks

The Future of Forests: Forecasting and Managing for Change Robert M. Scheller, NC State University Tues, July 15, 2025 | 9am PT Meet | Youtube Stream Hi all, The presentation will be via Meet and all questions will be addressed there. If you cannot attend live, the event will be recorded and can be found afterward at https://sites.google.com/modelingtalks.org/entry/the-future-of-forests-forecasting-and-managing-for-change More information on previous and future talks: https://sites.google.com/modelingtalks.org/entry/home Abstract Future forests will be shaped by pervasive change and where, when, and how society manages landscape change. But there is debate about whether active management has the capacity to accelerate adaptation to novel conditions, maintain resilience, and ensure the provision of ecosystem services.  Many innovative solutions have been proposed, including facilitated migration, genomic interventions, restoration silviculture, and others.  Few of these innovations have been tested at landscape scales because of the difficulties of testing and replication at broad scales and because the full effects may not be known for decades.  Landscape forecasting using spatial models has emerged as a powerful tool to test innovative strategies for managing landscape change and to assess how these strategies may interact with climate futures and novel disturbance regimes.  Landscape forecasting also provides information about the potential trade-offs and costs before adaptive strategies are implemented.  Dr. Scheller will describe the landscape forecasting framework, LANDIS-II, that he has co-developed and deployed over the past 20 years.  Using LANDIS-II, he has assessed forest change worldwide and concludes that for any landscape, a range of landscape trajectories are possible and that comprehensive management efforts have the potential to redirect trajectories towards more positive outcomes.  However, barriers to managing landscapes for change remain; these include the costs, local cultural identity, and the fear of uncertainty. Nevertheless, processes, tools, and technologies exist for overcoming social and ecological barriers to managing landscapes for change, and continued investment in social and scientific infrastructure holds out hope for maintaining healthy landscapes even as we enter an era of unprecedented change and disruption. Biography Dr. Scheller is Professor of Landscape Ecology and the Associate Dean for Research in the College of Natural Resources at North Carolina State University (NCSU). He grew up in Minnesota and received his B.S. from the University of Minnesota and Masters and Doctoral degrees in Forest Ecology from the University of Wisconsin-Madison. His research focuses on how landscapes have changed, how they will change, and why it matters. Anthropogenic change will transform many landscapes in the coming decades, in ways that exceed our imaginations. To understand past and future landscape change, he and his research group studies land use change and landscape history; forest and ecosystem and landscape ecology; anthropogenic drivers of change, particularly climate change; and policy and management. These diverse disciplines inform advanced forecasting tools developed by his lab, enabling local and regional decision-makers to assess the potential to manage for landscape change.

[Grigory Bronevetsky]

Video: https://youtube.com/live/BPNBPWa0GZc

Slides: https://drive.google.com/file/d/1I5xB-kh8GezsoBnIMBFaLRxzBpwSzRen/view?usp=sharing

Summary:

• Focus: modeling changing forests

• Disturbance change: wildfire, hurricane, pests, …

• Land use change: development

• Climate change

• Market forces: forest product demand

• Human adaptation to above

• We must manage forests with climate change in mind

• Key ecosystems and habitats

• Natural capital

• Environmental justice

• Forests change slowly: decisions now will have impact decades in the future

• Strategies:

• Persistence: maintain current landscape identity and values

• Resistance: maintaining identity

• Resilience: recovery from disruption

• Facilitated by: diversity, connectivity and organism movement, spatial heterogeneity,  Intermediate disturbance

• Management uses these features to promise persistence

• Transformation: 

• Focus on anticipating change and driving it to a desired equilibrium

• Approaches:

• Increasing or introducing disturbance

• Facilitated diversity/migration

• Preserving migration corridor

• Innovation

• Accelerate landscape conversion

• Genomic intervention

• …

• 
  

• Decline

• Accept future losses

• Ex: Sea level rise, desertification

• Strategies: abandonment, accept new state

• Simulation informs decision making and planning for forests

• Data science+scenarios -> Landscape Change model -> Projects of tradeoffs

• LANDIS-II: LANDscale Disturbance and Succession Model https://www.landis-ii.org/

• Processes:

• Succession

• Disturbances

• Anthropogenic Drivers: Harvesting, Fire Protection, Planting, Land use change, Climate change

• Optimized for ‘Landscapes’

• Typically 10k-10m hectares

• Forecast 50-100 years into the future

• Philosophy

• Built for collaboration

• Decentralized, distributed structure

• Management by 501(c)3 non-profit

• Distributed approach to evolving components

• Open-source

• C# language for low-barrier to coding complexity

• User-determined complexity

• Interface driven by text files and raster data

• User select/install needed extensions

• Spatially and temporally dynamic

• 2D grid of the landscape

• Tree populations evolve over time

• Trees grouped into cohorts

• Spatial processes: insects, harvests, forest, wind

• Applications by scientists across the world

• LANDIS-II @ 20 years lessons learned

• Collaboration is intentional, frequent meetings with the community, focus on shared values; takes time

• Tight budget has benefits: focuses team on developing key features, long-term needs

• Documentation is extremely useful for making model accessible

• Major lessons

• Every landscape is unique; no real “rules” of landscape change

• Adaptation can be effective but will need to be committed

• Need to make difficult choices and tradeoffs in landscape management

• Triage will be needed

• Beyond science, need to invest in social infrastructure to engage with stakeholders

• Need policy innovation

• Need to act before we know everything about forests

• Need more local experimentation and decision-making