Achieving social and ecological goals of coastal management through integrated monitoring

1Joint Institute of Marine and Atmospheric Research, University of Hawaiʻi at Mānoa, Honolulu, HI, USA; 2Ecosystem Sciences Division, Pacific Islands Fisheries Science Center, National Oceanic and Atmospheric Administration (NOAA), Honolulu, HI, USA; 3University of Hawaíi Social Science Research Institute, Honolulu, HI, USA; 4Habitat Conservation Division, Pacific Islands Regional Office, National Oceanic and Atmospheric Administration (NOAA), Tiyan, USA; 5Public Works Department, Marine Corps Activity Guam, Dededo, GU, USA; 6CSS Inc at NOAA National Centers for Coastal Ocean Science, Charleston, SC, USA; 7ARC Centre for Excellence in Coral Reef Studies, James Cook University, Townsville, QLD, Australia; 8Lynker Technologies, LLC. at Pacific Islands Regional Office, National Oceanic and Atmopsheric Administration (NOAA), Tiyan, GU, USA and 9School of Ocean Sciences, Bangor University, Anglesey, UK


| INTRODUC TI ON
Successful resource management relies on an understanding of the complex relationships between social and natural systems and their governance (Berkes et al., 2016). Taken together these interacting systems have been described as part of a social-ecological system (SES). Here, natural system refers to the biological and physical (biophysical) system and is used interchangeably with ecological system or ecosystem. Social system is used to characterize the interactions within and among human communities and their institutions, particularly those related to resource governance. The SES framework was developed to explain the many complexities of these relationships, but also to characterize what contexts and processes could help improve the management of natural resources (Ostrom, 2009).
More specifically, SES has been defined as 'a system that includes societal (human) and ecological (biophysical) subsystems in mutual interactions' (Harrington et al., 2010) or a system 'where social and ecological systems are mutually dependent' (Fidel, Kliskey, Alessa, & Sutton, 2014). Management is most successful when it maximizes the benefits that natural resources provide to people and human stewardship of the environment. To date, limited evidence linking conservation and natural resource management interventions to human well-being exists (McKinnon et al., 2016). Monitoring must adapt to capture this complexity, and in particular, focus sharply on the interactions and interdependencies of natural and social systems.
In the sustainability sciences, when monitoring is part of adaptive management, the purpose is to track ecosystem change over time, assess management implementation, and evaluate how well objectives were achieved (Kendall & Moore, 2012). Natural resource managers have monitored the biophysical status of ecosystems for decades; however, monitoring social systems has not been as well defined nor have the links between biophysical and social systems been adequately addressed (Wongbusarakum & Heenan, 2018). While conceptual frameworks for SES have advanced (Ostrom, 2009), practical approaches are needed to examine integration of these efforts requires additional capabilities and coordination to capture the complexities of interacting systems which operate at multiple scales (Fischer, 2018). It also requires scientists from different disciplinary backgrounds to be open to exploring new methods and willing to bridge disparate objectives, disciplinary epistemologies, and languages (Horlick-Jones & Sime, 2004).
Here, we discuss integrated monitoring (IM) as a coordinated long-term process in which scientists from multiple disciplines collect and analyse biophysical and social data to meet shared objectives of tracking, assessing and understanding changes over time in social and ecological systems and their interactions. Through merging datasets derived from varying methods, the goal of IM is to inform managers and policy makers about systemic changes and their linkages to achieving holistic natural resource management whilst promoting ecological health and human well-being. The limited number of guidelines and approaches for IM (e.g. Lindenmayer, Likens, Haywood, & Miezis, 2011;Wongbusarakum & Heenan, 2018) share common monitoring steps, including developing indicators relevant to management objectives, determining an appropriate sampling design, optimizing data collection methods, analysing and synthesizing datasets, and communicating results for adaptive management. We demonstrate how a causal model, a useful yet rarely implemented tool (Cheng et al., in review), can be applied to the monitoring process to illustrate plausible linkages among management strategies, changes in SESs, ecosystem services and human well-being.
We use Manell-Geus Habitat Focus Area (MGHFA) in Guam as a case study, to show practitioners how biophysical and social monitoring processes can be integrated into producing a holistic view of an SES.
We built on IM approaches outlined in the literature to design a baseline assessment of the MGHFA and adjacent coastal community. We used the merged results from biophysical and socio-economic data to develop a management approach linking management strategies and changes in SESs, ecosystem services and human well-being. We also used the baseline data to revise indicators for long-term IM and demonstrate how IM can support the dual pronged coastal management objectives of restoring natural habitats and building community resilience.
We discuss the practicalities of interdisciplinary collaboration in a realworld scenario and reflect on the successes and challenges posed when expanding traditional biophysical monitoring programmes to include human subjects and communities. Based on our experience of working with the stakeholders in MGHFA, we conclude with recommendations that could benefit future IM efforts in ecosystem management. unsustainable fishing practices and repeated coral bleaching (Burdick et al., 2008;Raymundo, Burdick, Lapacek, Miller, & Brown, 2017).

| Monitoring context
Sedimentation linked to land use practices is a major cause for the degradation of Guam's southern reefs (Burdick et al., 2008). Upland disturbances by wildfires lead to erosion and runoff, increased stream flow, sediment transport and streambank erosion (Camacho et al., 2016).
Increased frequency and severity of floods and sedimentation impacts both community safety and nearshore habitats (NMFS PIRO, in prep).
In 2010, the CRI initiated efforts to improve the condition of nearshore coral reef ecosystems by restoring upland areas thereby reducing sedimentation (Figure 2A). These efforts focused on the marine preserve, where the harvest of most fish species is pro-

hibited (The Territory of Guam & NOAA Coral Reef Conservation
Program, 2010). Limited public engagement in marine preserve management contributed to a lack of community support for watershed restoration. In response, BSP conducted a survey to elicit community conservation priorities and invited the community to participate in future planning efforts. The initial management model focused on biological targets, but was subsequently expanded to an ecosystembased management (EBM) approach that included priority ecosystem services and desired human well-being outcomes ( Figure 2B).
The modified approach aligned with the objectives of NOAA's Habitat Blueprint program (NOAA PIRO, 2017), which applies a national framework to improve habitat for fisheries, other marine life and coastal communities. In 2014, the MGHFA status was established with the goals: (a) improved coral reef ecosystem health; (b) improved community resilience to climate change impacts; and (c) enhanced community capacity to manage coastal resources. To achieve these outcomes, managers initiated an IM program to support evidence-based decisionmaking. The designation allowed managers to expand natural resource management activities to include human community resilience and refocus management efforts to systematically apply an SES framework.

| Implementing integrated monitoring
An interdisciplinary team was formed and included resource managers and aquatic, marine, terrestrial and social scientists from NOAA, CRI agencies, and the University of Guam. Together, they developed a monitoring strategy to assess the social and biophysical conditions of the MGHFA to inform adaptive management ( Figure 3). Indicators relevant to the MGHFA goals and the EBM model were identified (Table 1). The interdisciplinary team then evaluated existing data for the area. As these data could not fully inform management at the scale of the MGHFA, new baseline data were collected using a sampling design optimized for the watershed. The biophysical indicators were collected via habitat surveys and geospatial analysis, while social indicators were collected via household surveys, focus groups and key informant interviews.

| Using baseline results of integrated monitoring to adapt MGHFA management
The team synthesized the baseline datasets to update the conceptual management model (Figure 4). This model illustrates the complex linkages among: EBM strategies, expected changes in social-ecological conditions resulting from management, expected changes in ecosystem services and long-term outcomes in human well-being. The updated model and baseline results informed the development of three strategies to address the three primary MGHFA goals: (a) an ecological strategy to restore coastal environments; (b) a social strategy to involve the community in threat reduction and improve resource stewardship; and (c) a hybrid ecological and social strategy to reduce flooding and improve community safety and resiliency. These goals and strategies mutually support one another. After identifying target social-ecological conditions, the team included links between biophysical and social changes within the management model. Improvements in social-ecological conditions are expected to affect ecosystem services and human well-being outcomes, which in turn should inform adjustments to management strategies and activities. The changes in ecosystem services and human well-being are also expected to affect social-ecological conditions, including changes in human pressure on resources and stewardship. The next section details strategies for each of the three project goals.

| Improved reef ecosystem health goal: Watershed restoration strategy
The MGHFA ecological strategy is to reduce erosion, flooding and sedimentation, which have been linked with a decline in reef health F I G U R E 1 Manell-Geus Habitat Focus Area is located in southern Guam in Micronesia in the western Pacific (NMFS PIRO, in prep) (Burdick et al., 2008). In 2015, DoAg initiated reforestation projects in target sub-watersheds to reduce erosion. As reforestation takes over a decade to attain full effect, NOAA and BSP also implemented shorter-term measures, such as installing vegetative buffers and fibre rolls (NMFS PIRO, 2017). The expected improvements in water quality associated with reduced sedimentation should translate into F I G U R E 2 Evolving management approaches used in Manell-Geus. Initial management focused on biophysical outcomes (A). Over time, this was modified (B) to include ecosystem services and human well-being

| Improved community resilience goal: Flood reduction strategy
The flood reduction strategy is based on the initial baseline assessment which indicated that invasive bamboo (Bambusa vulgaris) exacerbates streambank erosion and flooding downstream, impacting both freshwater and marine fish habitat (Camacho et al., 2016). Flooding was also identified as a community concern, with over 50% of households  These indicators also track management performance.

| Engaged community capacity goal: Social preparation strategy
Habitat restoration success depends on community support. In turn, support requires an engaged community that understands the

| Adaptive management process
The integration of social and biophysical indicators in ecosystem monitoring informed adaptive management processes and improved management strategies and actions. Our case study demonstrates that IM can be implemented with limited funding and resources. Managers were hesitant to invest resources in monitoring instead of implementation activities.
However, through an iterative process, the team identified indicators that were informative, cost effective and repeatable. All indicators in Table 1 will be monitored every 5 years. Key indicators, such as benthic cover, coral health and fire and flood impacts will be monitored more frequently to inform adaptive management. To do this, the team partnered with existing biophysical monitoring efforts, including citizen science programmes, and is using qualitative and semi-quantitative data to monitor social indicators.

| RECOMMENDATI ON S FOR FUTURE INTEG R ATED MONITORING
Adaptive EBM is complex and should be informed by integrated approaches to monitoring and management. We recommend the following: It involved a multidisciplinary team that shared monitoring objectives to incorporate metrics tracking social and biophysical conditions. The team worked with coastal resource managers and stakeholders to link observed changes in each system with each other, with ecological targets, and with human well-being objectives. The key purpose, and also a challenge, of IM is to describe how social indicators may respond to changes in biophysical conditions over time, while simultaneously understanding how biophysical indicators are affected by social changes.
IM begins with different sets of disciplinary data, but the most meaningful analyses start once these data are brought together to complement each other, identify and/or fill knowledge or action gaps. This process leads to a better understanding of the complex relationships among the SES, as well as more comprehensive management that considers human communities and ecosystem interactions in their objectives. The MGHFA illustrates how IM allowed managers to shift from conventional biological targets to accounting for the complex connections, multiple pathways and multiple objectives of a SES. This approach has allowed managers to prioritize activities that benefit both ecological and social objectives in the MGHFA, and can serve as a model to support EBM in other contexts.

ACK N OWLED G EM ENTS
The National Oceanic and Atmospheric Administration's Coral Reef Conservation Program and Habitat Blueprint program supported this work. We thank the community members, stakeholders, scientists, resource managers and practitioners who contributed to the efforts towards IM. Comments and edits from all reviewers and science communications specialist of the earlier drafts helped improve the text and figures.

DATA AVA I L A B I L I T Y S TAT E M E N T
Data have not been archived because this article does not contain data.