Reimagining the Work(force) our Environment Needs: Why We’re Building a New Kind of Skills Taxonomy
Co-Written by JR Washebek
There are many gaps across the environmental workforce; we need to find them to close them.
Our ecosystems, and the tools we use to study and steward them, are changing—and changing fast. Evidence of that change can be acute, but the scale of impacts across communities and natural resources—our forests, wetlands, or rivers—gets clearer every year. We’re seeing hotter, longer fire seasons, more intense and variable weather events, and problems as wide-ranging as biodiversity loss, drinking water quality, and the deployment of new energy infrastructure. The challenge isn’t just the fact of that change, but—to quote one of my brilliant EPIC colleagues—the simultaneity of it.
Put differently: the disruptions are many, they co-occur across time and space in unpredictable ways, and with them come all sorts of novel planning, policy, and adaptation challenges for the thousands of agency teams and environmental practitioners tasked with protecting our communities and ecosystems. As we ask more and more of them, the clearer it becomes that old ways of defining, training, hiring, and developing that workforce simply won’t get the job done. Many agency leaders and practitioners across disciplines are rising to the challenge to be sure; but on the whole our workforce systems, skills models, education, training, and career pathways—even basic job descriptions—simply haven’t kept pace. Today’s shifting policy and technology landscapes also compound familiar (but widening) agency capacity gaps, and now all those factors seem to be converging faster than decision-makers in government, academia, or industry can respond.
Take existing skills or workforce planning frameworks, for example. Authoritative federal and industry competency schemes—including sector-specific accreditation programs, like forestry—all offer foundational guidance, and have shaped countless fields and career pathways over the decades. Yet they no longer reflect the full complexity or blurring boundaries in today’s environmental work; especially where data and digital technology are concerned. New tools, emerging work domains, and de facto multi-disciplinary job functions are often absent or inconsistently represented in traditional frameworks—and many role descriptions anchored to the standard models still fragment (or simply miss) tasks and fluencies that today, are deeply intertwined or rapidly evolving. Think of AI’s effects on things like environmental planning and public engagement, ecological modeling, data analytics, or broader policy design and environmental justice work.
Other examples outside the environmental domain may be even more instructive: the NIST National Initiative for Cybersecurity Education (NICE) Workforce Framework gave the federal government, industry, and academia a common language for cybersecurity roles and competencies, establishing a shared lexicon of tasks, knowledge, and skills that materially accelerated hiring, training, and talent mobility across a sector with similar cross-institutional complexity. The World Economic Forum also built a Skills Taxonomy that spans more than 100 economies and 13,000 skills. The Department of Labor (DOL) even published its own AI Literacy Framework earlier this year, establishing foundational areas and delivery principles for AI education across the public workforce system. Environmental management (and its vital adjacent fields) has no equivalent efforts. In other words, the sector most central to our sprawling national land use, energy, conservation, environmental health, and climate priorities is essentially operating without the kind of shared vocabulary every comparable domain takes for granted.
It’s also worth noting the discrepancies and gaps we see around skills like systems thinking, strategic stakeholder engagement, or ethical data use in various roles and settings. All are deeply human (or "soft") skills and yet essential in many of today’s dynamic environmental contexts. Yet they are rarely represented, taught, or rewarded explicitly in traditional frameworks or a myriad of training, hiring, or other talent and delivery settings. What’s more—at least where evolving technical skills and technology are concerned—disruptions are occurring at the task level rather than the job or occupation level. Standard occupational categories and job codes are structurally incapable of tracking where (for example) AI is actually changing the work, because they weren't designed to do so. Our measurement systems count jobs and occupations; but the shifts are happening inside those intensely contextual, and evolving, activities, as well as across the discrete tasks, workflows, and competencies that job titles don't clearly distinguish.
The point is that skillsets and workforce strategies must be made to correspond with the work we know needs doing across environmental agencies and domains—and without a planning tool structured at the task and competency level, we have no way to see what is changing, anticipate what might be next, or prepare workers and institutions alike to respond. That’s why we’re building a new kind of skills taxonomy—one that can help establish a baseline of where key skills and competencies cluster, as well as where they might diverge, overlap, or need to change. We’re building this resource so that leaders and practitioners across the numerous policy, field, research, governance, training, and technology settings that interact with environmental work can better clarify, anticipate, and ultimately close planning and delivery gaps. Our less modest goal is that the taxonomy—and later, its derivative products—also help decision-makers move beyond old models and disciplinary boundaries as they reimagine the sort of workforce our environmental priorities demand today and in the years ahead.
What’s in the taxonomy—and how might it be used?
The taxonomy itself is a structured classification of hundreds of competencies across seven core skills domains. Think about domains as the major work families representing broad but distinguishable areas of expertise: they naturally cut across disciplinary, training, and delivery boundaries and contexts—but basically serve as the functional areas that knit together related work activities and knowledge requirements. Domains each contain sub-domains, and those sub-domains include numerous examples of “hard” and “soft” skills—in many instances down to the task level or discrete technical areas where competencies live.
Taken together, that structure is designed to get users past generic role descriptions toward a more holistic—but practical—way of defining, mapping, and organizing the often cross-cutting or adjacent skillsets aligned to environmental efforts as diverse as drinking water data, forest restoration policy, wetland conservation, and biodiversity markets.
We see a variety of ways this tool might be used, but at this stage we're looking to experiment with “use cases” that span both supply and demand sides of the labor market—including education/training, recruitment, hiring, delivery, workforce development, and more. That includes, but of course isn't limited to:
Identifying current or emergent capacity gaps, including in discrete skill areas, teams, or delivery contexts (e.g., forestry, technology, environmental data)
Informing new hiring, job classification, role descriptions, and/or recruitment efforts
Supporting better credentialing and curriculum development efforts (including through public-private or other innovative partnerships)
Anticipating and preparing for technological transformations (AI impacts, changing data, policy, and technology landscapes)
Guiding training and up-skilling programs across environmental issue areas
Informing policy design or shaping workforce-relevant legislation and agency initiatives
One concrete example of the sort of gap analysis, role forecasting, and broader workforce planning efforts we hope this taxonomy will enable is accounting for how specific roles are—or should be—changing, and how position descriptions might be redesigned accordingly. For instance, consider how a federal forester’s work might be restructured to better reflect technical trends and opportunities tied to AI and remote sensing:
Finally, this taxonomy isn't just another ledger of buzzword-laden job titles. It’s the foundation for what we hope will become a dynamic workforce “intelligence” infrastructure—one designed to bridge what we call fieldcraft, datacraft, and statecraft, and in practice, provide a shared vocabulary for the skillsets needed to steward our environment in more innovative ways. Current skills domains include:
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Ecological and scientific knowledge forms the foundation of evidence-based environmental management. This domain is the foundational "fieldcraft" we talk about—from silviculture, restoration, and conservation biology, to hydrology or forest managment—and it remains the bedrock of many environmentally-focused professions. Professionals with strong capabilities in this domain translate complex ecological processes into actionable management strategies, conduct research that advances the field, and work to ensure that decisions are grounded in sound science. While some practitioners develop deep expertise in one area, increasingly complex environmental and policy planning challenges demand integration across multiple areas and collaboration (for example) with social scientists, engineers, policy experts, and communities.
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Technical and technology skills enable environmental professionals to build, procure, and leverage digital tools, do or leverage geospatial analysis, applied data science, and engineering—as well as emerging technologies—to make better decisions, work more efficiently, and tackle challenges at unprecedented speed and scale. In practice, this domain bridges traditional field-based environmental work with cutting-edge computational and data approaches. It also transforms how we monitor, analyze, and manage natural resources and build, use, and refine tools grounded in user research and built around human-ecosystem needs. These skillsets help maintain tech capacity in organizations, and in practice, link together the “datacraft” and (increasingly) digital technologies that are essential to improving technology delivery and environmental outcomes.
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These skills help build or maintain the organizational scaffolding needed to run complex, often multi-year, environmentally-focused projects and programs—and transform scientific knowledge and a team’s technical capabilities into real-world outcomes. This domain encompasses the essential skills for planning, organizing, and administering efforts and teams of various sizes and compositions—from managing individual projects to leading broader organizational strategy. Effective leaders can combine management competence with a deep understanding of ecological systems, policy environments, and diverse (sometimes conflictual) stakeholder needs.
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These are the operational competencies required for adaptive management. These skills translate plans, data, and science into tangible actions on a landscape. Professionals with strong field operations capabilities—whether in government, industry, the nonprofit sector, or somewhere in-between—bridge gaps between planning and outcomes, adapting proven techniques to site-specific conditions while integrating appropriate data and tools. In practice, this domain also includes the practical, hands-on work of assessing conditions, implementing wide-ranging management activities, responding to fires and emergencies, and maintaining the infrastructure, teams, and equipment that support field work. While some professionals specialize deeply in specific field skills, modern field professionals combine physical skills and field knowledge with technological fluency and data literacy.
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This domain is one of the areas where "statecraft" in its many forms plays a key role—especially the ability to translate between policy, science, and the lived experience, rights, and needs of local communities. In essence, communication and engagement skills are essential for turning environmental science, research, or management recommendations into action, building support for initiatives, and ensuring that diverse perspectives shape strategies and management decisions across boundaries of place and authority. From building new venues for collaboration or consensus-building, to moving discrete recommendations or policies from theory or “small-p" policy into implementation, this work supports the vital connective tissue between organizations and the places where our communities and ecosystems live.
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These skills form the essential framework within which all environmental management work and outcomes operate. That means they touch not only the legal, economic, and institutional knowledge needed to navigate complex regulatory settings and jurisdictions, but also the social, decision-making, and analytic abilities needed to evaluate, design, or implement policy—including by working across jurisdictional boundaries. It’s increasingly clear today that environmental challenges don't always reflect disciplinary or regulatory boundaries in practice, and hence, that effective policy professionals must integrate across skill areas, recognizing (for example) how carbon markets relate to environmental justice goals—or how land use planning, natural disasters, federal permitting policy, and judicial rulings affect everything from air quality in overburdened communities, to wetlands and drinking water quality. While some develop deep expertise in one area (such as restoration permitting, environmental data, or water policy) the most effective practitioners integrate multiple areas, collaborating across disciplines to address complex problems.
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This somewhat nebulous—but important—domain includes cutting-edge approaches to inherently complex environmental challenges, emphasizing novel and specialized skillsets that are increasingly crucial as land managers, agency leaders and teams, technologists, researchers, and others face evolving issues like climate change, the ecosocial impacts of artificial intelligence, and biodiversity loss. Accordingly, these skills represent frontiers in environmental management, incorporating new and emergent technologies, innovative financial mechanisms, and forward-thinking approaches to quickly evolving efforts in areas like biodiversity markets, new infrastructure deployment, sustainable agriculture, and other innovative work in restoration, conservation, mitigation, or environmental permitting (for example).
By collapsing so many skill areas and wide-ranging functions into these core domains, the taxonomy allows us to zoom out and to zoom in—to layer, apply, and compare analytically-useful "lenses” onto the many elements and factors that make up and shape this workforce. For example, assessing which roles may be most exposed to technological disruptions like AI, where career pipelines might be most vulnerable, or how best to forecast the discrete—but often fragmented or outdated—skillsets tied to emerging priority areas like adaptive forest management. In practice, we see the taxonomy enabling three kinds of work that the field currently has no good tools for:
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Federal environmental agencies are deploying AI tools without a common specification of what the surrounding workforce needs to know to use them responsibly. The taxonomy provides the first sector-specific framework for defining AI fluency in environmental practice—not as a generic digital literacy concept, but as a structured set of competencies grounded in how things like ecological modeling, environmental permitting, natural resource monitoring, and field operations actually work. That specification is the prerequisite for any serious effort to build, hire, or develop AI-ready environmental teams.
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Critical minerals extraction, infrastructure permitting, energy development, and habitat conservation all require overlapping competency sets, but workers can’t easily move across those sector boundaries because no shared language exists to make their qualifications legible. A restoration ecologist with remote sensing expertise and NEPA permitting experience has skills directly relevant to critical minerals site assessment—but no credential system currently recognizes that transfer. The taxonomy is the sort of instrument that could make that recognition possible, enabling talent mobility precisely where we see barriers and/or the most concentrated demand.
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Workforce measurement systems that can’t track task-level change can’t generate the evidence needed to evaluate training investments, anticipate emerging gaps, or target policy interventions. Mature versions of this taxonomy, maintained as open-source public infrastructure, could provide the shared measurement architecture that states, agencies, professional associations, and universities need to coordinate on workforce development—without reinventing incompatible frameworks in parallel or isolation. This is what sector-specific workforce infrastructure looks like before it becomes invisible; before it's simply the thing everyone uses.
For all its nuance, though, the theory of change that underpins our framework and its many layers is simple: fostering the enabling conditions for better results—cleaner air and drinking water, better and faster conservation, restoration, or permitting outcomes—starts with getting the right people, process, and tools in place. In practice, that means getting technical talent into (or partnering closely with) agency teams in ways that actually empowers them to team, learn, iterate, and deliver better outcomes.
Looking Ahead
Clarity around the many skills that should make up a modern environmental management workforce is hard to capture, and the last thing we want is to imply we have all the answers—or to build this tool in a vacuum. Our taxonomy and the future assets we hope to erect on its foundations are intended to be open source public infrastructure; a set of evolving resources we hope that states, NGOs, professional associations, and federal agencies alike can help us to refine and leverage in improving their own workforce strategies and delivery capabilities.
In the coming months, we’ll be releasing a series of deep dives into this work as well as the first interactive version (v1.0) of the taxonomy itself. But we’re actively looking for partners who want to test-drive its constructs against a real-world workforce planning challenge with us. Whether that’s developing better forestry workforce pipelines, building out environmentally-focused data teams, or redesigning how you scope and hire technical roles, we want to hear from you.
