There are a number of challenges that agencies and stakeholders face when approaching AM. The most prominent of these barriers include: insufficient capacity, problems with organizational culture and structure, inadequate or uncoordinated data collection, and challenges associated with conforming to existing legal requirements.
Capacity
Many of the most significant barriers to AM are related to the ability of agencies and stakeholder groups to provide the time, personnel, and fund-ing needed to determine appropriate restoration objectives and monitorfund-ing questions, develop a rigorous monitoring program that includes feedback mechanisms, and coordinate among many different stakeholders (Walters 1997, Lee 1999). Monitoring is especially vulnerable to a lack of resources and is often the first program cut when budgets shrink (Doremus 2008).
This is especially problematic for the long-term monitoring needed to track changes and trends at the landscape scale (Moir and Block 2001, Nichols and Williams 2006). Legislation, like the Forest Landscape Restoration Act provides an avenue to correct this bias by explicitly requiring monitoring as a condition of receiving funding.
Organizational Culture and Structure
Adaptive management represents a new way of conceptualizing manage-ment and decision-making (Stankey et al. 2003). AM requires managers to openly acknowledge the uncertainty inherent in management objectives, prescriptions, and the systems being restored (Smith 2009). However, if an agency’s culture is more focused on outputs than providing the time and resources necessary to evaluate and improve management actions, agency
personnel may find it difficult to justify allocating resources to a project where the outcomes are acknowledged to be uncertain (Allan and Curtis 2005). It may also be challenging to justify the short-term risk inherent in an active AM strategy, despite its long-term benefits (Stankey et al. 2003).
Institutional structures also present challenges to applying AM at the landscape scale. Since most natural resource agencies, including the USFS, are characterized by a hierarchical chain of command, there is a strong tendency for top-down decisions that can limit flexibility, participation, and innovation at the local level (Johnson 1999, Allan and Curtis 2005, Jacob-son et al. 2006). In light of these challenges, managers should be clear and transparent about the uncertainties and risks to be balanced in any deci-sion. Managers at higher levels can also offer clear guidance, support, and incentives for AM in the field to encourage experimentation and long-term learning.
Inadequate or Uncoordinated Data Collection
Data collection systems that are deficient or lack organization create added challenges for otherwise sound AM programs. For example, if the USFS collects different data across ranger districts, if resource specialists collect data using different methods and if corporate databases are incompatible with certain types of data or collection methods, then the design and imple-mentation of a robust and cost-effective monitoring program are limited.
Moreover, the learning and adaptation that could come from using that information are compromised. Successful AM requires that data be collected and interpreted in a way that they are useable, often by multiple parties (Doremus 2008).
Various database solutions are being proposed to create a home for data collected under multi-party monitoring programs. For example, the Uncompahgre Plateau CFLRP project in southwestern Colorado is employ-ing CitSci, which is a support system for citizen science-based monitoremploy-ing.
Other groups (e.g., 4FRI, SWCC, and FRRT) employ monitoring coordi-nators or consultants to aggregate and analyze data from various sources, as well as make suggestions for improving collection and storage methods.
Conforming to Existing Legal Requirements
Guaranteeing that AM conforms to substantive and procedural legal stan-dards, such as those found in the Endangered Species Act (ESA), NEPA, and Federal Advisory Committee Act (FACA), is a significant barrier to AM. Under the ESA, AM may, or may be perceived to, impose risks that violate the precautionary standards of the law (i.e., not placing a listed species in jeopardy; Volkman and McConnaha 1993, Doremus 2001, Stankey et al. 2003). However, AM has been successful in cases involving the ESA, such as the Northwest Forest Plan and in Biological Opinions for operation of the Sacramento and San Joaquin River System (Ruhl and Fischman 2010, Schultz and Nie 2012).
Under NEPA, managers must describe in an EIS (or Environmental Assessment for less complex actions) all possible adaptive measures they may undertake and ensure that any future effects are within predicted ranges. This may be challenging given uncertainties, and agencies may
A high school student takes tree height measurements for the Uncompahgre Plateau project. The UP project incorporates citizen science-based monitoring into its AM plan. Photo courtesy of ERI
be reluctant to undertake AM if future management adjustments might require supplemental analysis (see Chapter 3, also Schultz and Nie 2012).
However, management changes will not always require NEPA supplemen-tation. It is possible to write NEPA documents with monitoring commit-ments that are enforceable over time, not only by requiring supplementa-tion, but also by requiring monitoring data to be available before new actions are taken (Blumm and Bosse 2007, Schultz and Nie 2012).
Finally, the requirements of the FACA may pose barriers to the formal participation of collaborative groups in federal agency decision-making, es-pecially in the early stages of the NEPA process (Benson 2009). Likewise, FACA may, or may be perceived to, limit agency representation on com-mittees, such as those discussing monitoring and desired conditions under the CFLRP. However, there is ample room for stakeholders and agencies to work together on developing and implementing AM frameworks and monitoring plans, as long as federal land managers retain their formal decision-making authority and facilitate an inclusive public involvement process (see Chapter 1).
Data is collected for a wetland restoration project. Photo courtesy of ERI