Deviating from the Plan
Authors: Murenbeeld Kathryn Joyce 
Published: September 2022

Forests are under increasing stress due to changes in disturbance regimes, such as wildfire and pest or disease outbreaks, an
increase in more severe and prolonged drought, and changes in land use. These stressors are already having an observable impact
on forests in the western United States. Many forests within the western US are managed by the US Forest Service. Forest management
is important as a tool for increasing a forest's ability to withstand or recover from these stresses. Additionally, because of the
forest’s influence on interactions between the land surface and the atmosphere, forest management has implications for future energy,
water, and carbon cycles. However, management is driven by socio-economic, political, and ecological needs which can influence the timing
of management activities. Forests are dynamic ecosystems, and changes to the timing of management through delays could lead to unanticipated
impacts on a forest’s structure, productivity, and ecohydrological function. Land surface models (LSMs) are one tool used to investigate land
surface processes and land-atmosphere interactions. LSMs represent vegetation dynamics in different and increasingly sophisticated ways. While
the fidelity of plant biophysical and biogeochemical process representation has increased in many of these models, the representation of forest
management is still very simplistic. Until recently, the temporal aspects of management have rarely been included in studies using LSMs. Here,
we addressed this challenge by including the temporal details of representative timber harvest activities from the western USA within LSM
simulations. We hypothesized that changes in the timing of management activities can have long term impacts on the structure and functioning
of a forest. To test this hypothesis, we quantified vegetation management activities in the western USA and investigated the role specific project
characteristics have on potential project delays. As a proof-of-concept, we used this data to inform the timing of single point scale logging
simulations using the Functionally Assembled Terrestrial Ecosystem Simulator of the Community Land Model (CLM-FATES) for a ponderosa pine dominated
forest in southern Idaho. A challenge encountered in simulating realistic forests was a bias towards smaller-diameter trees (i.e., < 50 cm diameter
at breast height), relative to observations. In overcoming this challenge, we expanded on current work within the CLM-FATES and greater LSM community
to better parameterize the model for temperate, evergreen forests. We developed methods to generate multiple parameter ensembles and simulated these
ensembles under different climate forcing and coexistence conditions. Over the course of this work, we developed significant and important overarching
findings about critical facets of simulating managed forest ecosystems. First, we found that environmental regulations (here the type of NEPA analysis
required for a project), the length of time to complete that analysis, and the type of management activity had the biggest impact on the probability of
project implementation. Second, from logging simulations, we found that the timing of treatments can have long term impacts on the resulting forest
size-structure, but timing has less of an impact on the long-term functioning of the forest as indicated by the model. Third, more complex
ecosystems – as represented by the addition of an additional plant functional type – can lead to more realistic distributions of tree size
classes, although this added ecosystem complexity does not appear to assist in identifying optimal sets of model parameters in CLM-FATES. This
work makes an important contribution to deploying sophisticated, demography based LSMs in western US forests by demonstrating how models can now
capture legacies of human interventions and that calibration of model parameters is complex and constrained by the existing structure and makeup
of these systems. These results highlight the importance of representing different aspects of human systems in ecosystem models as well as
highlighting the tension between a need to improve model calibration without increasing model complexity.