Growing Through Decay: A Case for Regenerative Scholarship

When a 400-year-old Douglas fir crashes to the forest floor, it begins its most important work. For centuries, this tree sequestered nutrients in its massive trunk, created deep shade that prevented most other plants from establishing, and dominated the local ecosystem through sheer persistence. Its death seems catastrophic—a landmark disappearing, decades of wildlife habitat destroyed, the canopy suddenly opened to harsh weather.

But ecologists see something different: the beginning of the forest’s renewal. As the fallen giant decomposes, it releases nutrients that have been locked away for centuries. The gap in the canopy allows light to reach species that have waited in dormancy for this opportunity. Within a few seasons, the dead tree becomes a “nurse log”—a raised bed where countless seedlings take root, fed by the decomposing wood beneath them. The forest doesn’t just survive the tree’s death; it depends on it.

I think about this process whenever I encounter academic sustainability discourse, particularly around Digital Humanities projects. But here’s where language gets slippery. There’s a difference between keeping something unchanged (preservation) and keeping something alive (sustainability). The problem is that in practice, academic “sustainability” often defaults to preservation thinking—and more often than not, keeping something alive ends up looking like preserving a status quo that has become very much not alive.

When scholars talk about sustaining their projects, what are they really trying to sustain? The intellectual insights? The methodological innovations? The institutional structures that employ them? The symbolic capital accumulated through years of work? These aren’t the same thing, though we often speak as if they were.

The Nurse Log Problem

A recent blog post about DH sustainability describes a research team struggling with knowledge transfer. When a key programmer leaves, the remaining staff scrambles through “intense daily meetings” to absorb years of undocumented decisions. The project’s workflows have become “so interconnected” that breaking them into teachable components proves nearly impossible. The authors frame this as evidence that projects need better “human infrastructure”—more mentoring, more relationship-building, more careful cultivation of institutional knowledge.

But notice the slippage between different kinds of sustainability here. Is the goal to sustain the specific technical solutions this programmer developed? The capacity to work with Arabic manuscripts in digital formats? The employment of skilled technical staff? The continuation of this particular research group? Each of these requires different strategies and resources, yet they get bundled together under the umbrella of “project sustainability.”

From a forest perspective, this bundling reveals something else: The massive tree—the experienced programmer with years of embedded knowledge—has become so central that the entire ecosystem depends on its continued existence. But ecological sustainability works differently. When a dominant tree falls, the forest doesn’t try to keep it standing; it creates conditions where new growth can emerge from the nutrients released by its decay.

Because what grows in the shadow of a giant tree?

Very little.

The underbrush remains stunted, dependent on occasional filtered light, never developing the robust root systems needed for independent growth. When the tree finally falls, these understory plants often die too—they were adapted to dependence, not autonomy.

These are legitimate concerns, but they shape sustainability thinking in ways that can work against actual intellectual vitality. I’ve felt this tension myself—the way project deadlines and funding cycles push toward keeping what’s working rather than experimentation with what might work better—or better. When keeping a project alive becomes primarily about keeping people employed or institutions prestigious, the project itself can become zombie-like—technically functional but no longer generating new insights. We end up preserving structures rather than sustaining capacities.

Forest Succession vs. Institutional Accumulation

Ecologists distinguish between different stages of forest succession. Early succession—the burst of diverse growth that follows disturbance—looks chaotic but serves crucial functions. Fast-growing pioneer species stabilise soil, fix nitrogen, and create microclimates that eventually allow slower-growing climax species to establish. Each stage prepares conditions for the next, and no stage is permanent.

Academic institutions, by contrast, operate on accumulation models that conflate preservation with sustainability. Every new department, program, or research centre gets added to existing structures. Every innovation becomes a permanent feature requiring ongoing maintenance. We build knowledge like sedimentary rock—layer upon layer, with each stratum supporting the weight of everything above it.

But preservation thinking creates brittleness. When we try to sustain everything, we often sustain nothing well. Resources get spread thin across maintenance obligations. Innovation slows because change threatens existing investments. What began as sustainability—keeping good work alive—becomes its opposite: institutional inertia that prevents new life from emerging.

But sedimentary systems become brittle. They resist change, develop pressure points, and eventually experience catastrophic failures when accumulated stress exceeds structural limits. Forest succession offers a different model: cyclical renewal, where each stage contains the seeds of its own transformation.

Consider how we typically approach a successful DH project. The work produces valuable outputs, receives recognition, attracts additional funding. The natural institutional response is to preserve—they would probably say “sustain”—and expand—hire permanent staff, acquire dedicated server space, develop ongoing curricula around the project’s methods. Within a few years, what began as experimental work has become infrastructure requiring indefinite maintenance.

This isn’t necessarily wrong, but it follows the logic of preservation rather than succession. We’re trying to keep the climax forest in perpetual maturity, preventing the disturbances that would allow new forms of growth to emerge. Meanwhile, resources flow toward maintaining existing projects rather than enabling new experiments.

The Economics of Decomposition

I calculated once what full sustainability would cost for a modest DH project following standard preservation guidelines. Beyond basic server maintenance, true sustainability requires ongoing technical support, regular data migration, staff training for knowledge transfer, and institutional commitments that can span decades. My estimate came to roughly 0.5 FTE per project annually—half a person’s working life devoted to maintenance rather than creation.

But the real problem isn’t the absolute cost—it’s how accumulated maintenance obligations shape institutional decision-making. A colleague is working at an institution where they maintain three different mapping platforms because different projects were built on different technical foundations over the past decade. Each requires specialised knowledge to maintain. None can easily share data with the others. When someone proposes a new mapping project, the conversation immediately turns to compatibility with existing systems rather than what approach would best serve the research questions.

This is path dependency in action. Past technical choices don’t just require ongoing resources—they constrain future possibilities. The brilliant GIS specialist I know spends half her time troubleshooting legacy databases and half her time explaining to new faculty why their innovative project ideas won’t work with existing infrastructure. Her expertise gets channelled toward maintaining what “is there” rather than imagining what could be built.

I see this pattern everywhere. The digital humanities programmer whose days are consumed by migrating old XML files to new servers. The graduate student who learns TEI encoding not because it’s the best tool for their research, but because that’s where the preserved data lives. The department that turns down exciting collaboration proposals because they would require technical approaches that don’t align with current maintenance—pardon, sustainability—capacities.

Like a forest where no trees are allowed to fall, eventually the canopy becomes so dense that no light reaches the ground. It’s not that maintaining mature trees is inherently wasteful—those trees provide valuable ecosystem services. But when sustainability-as-preservation becomes the primary organizing principle, new growth becomes increasingly difficult to sustain.

Real forests solve this through decomposition—the complex process by which organic matter breaks down and becomes available for new use. A fallen Douglas fir doesn’t disappear; it becomes a nurse log that feeds dozens of different species over decades. The nutrients locked in its massive trunk gradually release, supporting plants that couldn’t survive in the tree’s shadow.

Academic work could learn from this model. Instead of trying to maintain every technical solution indefinitely, we could focus on ensuring that valuable insights decompose into forms that future scholars can use. This might mean extracting key datasets into standard formats while letting custom interfaces die. Publishing methodological insights as transferable principles rather than preserving specific software implementations. Creating documentation that enables reimplementation rather than requiring ongoing maintenance of original systems.

Ecological Niches and the Politics of Intellectual Extinction

Healthy forests maintain diversity through spatial and temporal niches. Different species thrive in different conditions—some need full sun, others prefer shade; some establish quickly after disturbance, others require decades to mature. This diversity creates resilience; when disease or climate change affects one species, others can expand to fill available space.

Academic sustainability discourse often works against this kind of diversity. We develop “good practices” that become institutional standards, funding priorities that shape entire fields, research data protocols that favour certain types of work over others. Projects that don’t fit established categories struggle to continue, not because they lack intellectual merit but because they don’t align with our sustainability endeavours and preservation infrastructure.

The DH project described in the blog post developed innovative approaches to Arabic manuscript encoding, creating custom tools that served their specific scholarly needs better than existing standards. But this innovation came at the cost of long-term interoperability—their solutions work beautifully for their materials but don’t transfer easily to other contexts.

From a sustainability perspective, this looks like a problem requiring better planning and institutional support. From an ecological perspective, it looks like successful adaptation to a specific niche. The question isn’t how to make these innovations persist indefinitely, but how to ensure that future scholars facing similar problems can develop equally innovative solutions.

But who decides what gets to decay and what gets preserved? This is where the forest metaphor shows its limitations—in academia, unlike in ecosystems (possibly?), these decisions are never neutral. The projects that receive sustainability funding usually align with established institutional priorities, come from well-connected researchers, or address problems already recognised as important.

Meanwhile, work that challenges dominant frameworks, emerges from marginalised perspectives, or asks inconvenient questions often lacks the social and institutional support needed for preservation. The sustainability discourse can become another mechanism for maintaining academic hierarchies—ensuring that established approaches persist while experimental or critical work dies from neglect.

The Mycorrhizal Network of Ideas

Forests maintain underground networks through which trees share resources and information. Mycorrhizal fungi connect root systems across species, allowing established trees to support new growth and enabling the forest to respond collectively to environmental changes. But here’s what’s remarkable: these networks often matter more than what’s visible above ground. A forest’s resilience depends less on any single organism’s health than on the fungal web that connects them.

The most important knowledge transfers in academia happen through similar underground networks. Not the formal collaborations that appear on grant applications, but the casual conversations at conference coffee breaks. Not the official mentorship programs, but the impromptu troubleshooting sessions where someone shares a crucial workaround. Not the documented methodologies, but the embodied expertise that moves when people change jobs.

I think about the digital humanities programmer I know who left one institution for another, carrying in her head the solutions to dozens of encoding problems that were never written down anywhere. Within a year, her new colleagues were using approaches that had taken her old team years to develop. The knowledge travelled through her migration, not through any documentation or preservation system.

But academic institutions often treat these networks as problems to be solved rather than ecosystems to be nurtured. We create formal documentation requirements that turn living knowledge into static text. We establish “knowledge management systems” that capture information while killing the relationships that made it meaningful. We try to preserve institutional memory by preventing people from leaving, not realising that movement is often how knowledge stays alive.

The blog post describes how the DH project’s principal investigator fostered “intellectual trust and distributed agency” through unstructured one-on-one meetings and deliberate avoidance of micromanagement. This sounds positive, and it probably was. But it also reveals something troubling about how academic knowledge networks actually function.

What happens to “distributed agency” when it depends on one person’s management style? If intellectual trust requires ongoing cultivation by a particular leader, how distributed is it really? The very language suggests a kind of benevolent hierarchy that mycorrhizal networks don’t have—no single organism controls the underground web that keeps the forest alive.

Mycorrhizal networks redistribute resources automatically. When a tree is attacked by disease, the network can shift nutrients to support its recovery. When an old tree dies, its accumulated resources flow to younger plants that need them most. The system operates through biochemical signals that bypass conscious decision-making entirely.

Academic networks, by contrast, are often disrupted by exactly the kind of conscious management that institutions favour. I’ve watched departments hire “collaboration coordinators” whose job is to facilitate the informal connections that used to happen naturally. The result is usually meetings about collaboration instead of actual collaboration, documentation of relationships instead of living relationships.

Sometimes the most productive academic networks emerge despite institutional structures rather than because of them. The late-night problem-solving sessions that happen when official support has gone home. The unauthorised sharing of proprietary software that makes certain research possible. The informal mentorship that crosses hierarchical boundaries because someone needs help and someone else has knowledge to share.

These networks resist certain understandings of sustainability in the ways that institutions typically recognise. How do you sustain “intellectual trust”? How do you transfer “distributed agency” to future projects? How do you document the kind of knowledge that exists only in the relationships between people?

Perhaps the answer is that you don’t—and maybe shouldn’t? Like mycorrhizal networks, these systems work through living connections that must be re-established in each new context. The goal isn’t to preserve specific relationships but to maintain conditions where productive relationships can form. This might mean creating fewer formal structures rather than more. Leaving space for serendipitous encounters. Allowing knowledge to move through unofficial channels. Allowing the most valuable insights to find their own paths

Regenerative Scholarship: A Different Growth Model

What would academic work look like if it followed forest succession rather than institutional accumulation? Instead of trying to preserve every innovation indefinitely, we could create conditions for ongoing intellectual renewal.

I don’t have all the answers, but I’ve been experimenting with some approaches that feel more ecological than preservational or even sustainable.

Design for obsolescence as ecological strategy. What if we built projects with explicit end dates, like forest management cycles? I’ve started including “sunset clauses” in my own grant applications—specific points where we’ll evaluate whether continuation serves the work or just serves our attachment to the work. This feels risky in a culture that measures success by longevity, but I wonder: could a three-year project with a clear endpoint actually accomplish more than an indefinite project that drifts?

Some digital humanities centres are experimenting with this. Instead of promising permanent hosting for every project, they offer five-year commitments with explicit migration paths. The question becomes: what do you need to extract from this work before we let the original infrastructure die? It changes how you design things from the beginning.

Practice succession thinking over preservation thinking. What if we recognised that experimental methods and mature methodologies need different kinds of support, like pioneer species and climax forests? Early-stage digital humanities work might need rapid prototyping funds and permission to fail spectacularly. Established methodologies might need different resources—infrastructure for large-scale application rather than innovation grants.

I think about how some scientific fields handle this naturally. Physics supports both theoretical speculation and large experimental facilities, recognising these serve different ecological roles. But humanities funding often treats all work as if it should be permanent and polished from the start. What would change if we explicitly funded “pioneer scholarship” that’s meant to be fast, experimental, and expendable?

Invest in soil, not trees. Instead of funding individual projects indefinitely, what if we invested in conditions where good projects could keep emerging? This might mean funding graduate student training in transferable skills rather than project-specific expertise. Or supporting collaborative infrastructure that can host multiple temporary projects rather than maintaining single permanent installations.

I’ve seen libraries shift in this direction—instead of preserving every digital collection identically, they’re investing in migration tools and format standards that can support many different sustainability strategies. The infrastructure becomes more important than any particular collection.

Embrace intellectual decomposition. What if we shared work in forms designed to be reimagined rather than cited intact? I’ve been experimenting with publishing methodology descriptions separately from specific implementations—hoping others will adapt the approach for problems I never considered. It’s uncomfortable to release control like this, but what if misinterpretation is actually a sign that an idea is robust enough to endure?

Some scholars are trying “open notebook” approaches where process gets shared continuously rather than just final products. The work becomes available for decomposition while it’s still alive. Others publish datasets with explicit invitations for reanalysis. These approaches feel vulnerable, but maybe vulnerability is what enables actual intellectual fertilisation.

Cultivate disturbance. What would it look like to deliberately end things that are working well but have reached their limits? Some institutions experiment with sabbatical programmes that require faculty to abandon their established research areas entirely. Others retire successful programmes after fixed periods to make space for new approaches.

This feels almost unthinkable in our current academic culture, but I wonder: what innovations never happen because all our energy goes toward maintaining what already exists? What if we created rituals for intellectual endings that felt celebratory rather than tragic?

Question preservation privilege. Whose work gets sustained and whose gets abandoned? I’ve noticed that projects led by established scholars often receive preservation resources that experimental work from junior researchers doesn’t. Sometimes refusing institutional preservation becomes an act of solidarity—letting your ideas persist through adaptation rather than claiming permanent space in institutional memory.

The old-growth forest doesn’t preserve individual trees—it preserves the conditions under which forests can continue to grow, die, and regenerate. Academic institutions could learn from this restraint: creating robust conditions for intellectual life rather than elaborate systems for preventing intellectual death.

The most sustainable scholarship might be that which refuses institutional sustainability—work that releases its insights into contexts the creators never controlled or anticipated. This isn’t reckless abandonment but strategic dispersal, like the way certain plants have evolved to scatter seeds widely rather than clustering them protectively around the parent.

I think about scholarly work that has moved far from its original disciplinary home—concepts that migrated from one field to another, methodologies that got picked up and adapted in unexpected ways. These ideas didn’t persist because they were carefully preserved in their original form, but because they were portable enough to establish themselves in new intellectual environments.

Like seeds scattered by dying trees, these ideas find their own soil, establish their own roots, and grow into forms their creators never imagined. The sustainability happens through dispersal and adaptation, not through institutional maintenance.

But I’m still learning how to practice this.

How do you balance intellectual generosity with career security?

How do you design for obsolescence in systems that reward permanence?

How do you cultivate disturbance without just creating chaos?

These questions feel urgent as our institutions strain under accumulated sustainability obligations and budget cuts at the same time. The answer might not be better sustainability planning, but different relationships to intellectual mortality—seeing death and decay not as failures to prevent, but as necessary conditions for new life to emerge.

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A Note on the Original Blog Post

The blog post that sparked this reflection—”People Behind the Interface: Sustainability as a Social Process in DH” (LINK)—deserves recognition for what it accomplishes. Through careful interviews with three team members at different career stages, it captures something often missing from academic discourse: the lived experience of working on collaborative projects over time. The authors resist the temptation to abstract away the messy human realities of knowledge transfer, staff turnover, and relationship-building that actually hold digital scholarship together.

Yes, at times, I experienced a whiff of romanticising collaborative work in ways that might not reflect everyone’s experience. The unstructured meetings, the distributed agency, the intellectual trust—these sound almost too good to be true, and probably were for some team members who didn’t make it into the final interviews. I kept thinking about colleagues who thrive with clear documentation rather than relationship-heavy knowledge transfer, or who find those lengthy one-on-one meetings exhausting rather than energising. What about the team members who prefer structured processes to distributed agency, or who work best when expectations are explicit rather than emergent?

But that’s not really the point.

What matters is that someone took the time to document how academic collaboration actually unfolds over time, with all its dependencies and vulnerabilities. The question of what sustainability feels like for the people living it remains largely unasked—and that’s perhaps what made me want to write this response. Because when you read between the lines of those interviews, you start to wonder: did this actually feel sustainable to the people involved?

That question sent me down a three-hour writing rabbit hole that became this piece. I’ve left it largely as it emerged—probably some repetitions, definitely some contradictory thoughts, and certainly more questions than answers. The original blog post opened a conversation. This is just my contribution to keeping it going.

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Image: © Victoria Mummelthei rabbitingyears

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