The critical social processes for standardising the ecological monitoring of Australian landscapes

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Bardsley, Ben Sparrow This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4337606/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Sep, 2024 Read the published version in Environmental Management → Version 1 posted 11 You are reading this latest preprint version Abstract The social aspects of ecological monitoring are often overlooked. Ecological monitoring provides vital information for decision-makers and natural resource management practitioners to make informed environmental management decisions. For a long time, ecological monitoring across Australia has utilised a wide variety of different methodologies resulting in data that is difficult to analyse across place or time. Much of the ecological data that is currently generated in incomparable with other data or it has been collected using inappropriate methods for the intended aims. In response to these limitations, a new systematic approach to ecological monitoring has been developed in collaboration between the Terrestrial Ecosystem Research Network and the Australian Department of Climate Change, Energy, the Environment and Water - the Ecological Monitoring System Australia. We found that environmental management stakeholders are not opposing the standardisation of ecological monitoring. However, key concerns emerged regarding the capacity needed to implement the standard protocols, the utility of the resultant data for regional projects, and the adaptability of the EMSA. Stakeholders emphasised the need for autonomy and flexibility, so their participation in protocol development can facilitate regional adoption of the standards. Respondents’ concerns about a perceived lack of genuine consultation and acknowledgement of feedback revealed the importance of clear communication at all stages of an environmental management project aiming to standardise practices. New approaches to environmental management will increasingly have to account for the complexity of socio-ecological systems in order to overcome the unprecedented challenges that will arise in the wake of future global change. ecological monitoring standardisation natural resource management socio-cultural challenges social learning Australia 1. Introduction The social aspects of ecological monitoring are often overlooked. Ecological monitoring provides vital information for decision-makers and natural resource management (NRM) practitioners to make informed environmental management decisions. Successful monitoring measures ecological change (by effectively providing baseline data) and informs a range of decisions, actions and research relevant to environmental management policy and practice (Burns et al., 2018 ). Monitoring methods need to quantify current ecological condition in a manner which enables the forecasting of ecosystem change to improve risk management and sustainable economic and social development (Lindenmayer et al., 2015 ). Such monitoring continues to be funded and conducted, and the resultant data interpreted and utilised by stakeholders whose varying interests and objectives inevitably influence their work in different ways. Nonetheless, the implications of those social processes are under-represented in the literature. For a long time, ecological monitoring across Australia has utilised a wide variety of different ecological monitoring methodologies resulting in data that is difficult to analyse across place or time. Much of the ecological data that is currently generated is difficult to compare with other data or it has been collected using inappropriate methods for the intended aims (Likens and Lindenmayer, 2018 ; Sparrow et al. 2020a; Sparrow et. al. 2020b). In response to these limitations, a new systematic approach to ecological monitoring has been developed as a collaboration between the Terrestrial Ecosystem Research Network (TERN) and the federal Department of Climate Change, Energy, the Environment and Water and has been called the Ecological Monitoring System Australia (EMSA). It is guided by specified ecological field survey modules, or protocols, and associated data systems, and aims to generate a national dataset to improve data collection, storage and access (TERN, 2024 ). While implementing such a transformation in scientific approach will require many technical adjustments, it is also essential that the social aspects of ecological monitoring are considered to ensure the uptake and adoption of these long-term monitoring programs. This article describes research undertaken to understand the key socio-cultural processes relevant to developing a systematic monitoring program for Australia. New challenges continue to emerge for Australian environmental, social and economic systems largely driven by environmental change. To understand this change, a new systematic monitoring system is being implemented across terrestrial landscapes to ensure that the resulting evolution in ecosystems can be understood by scientists, policy makers, and the general public (Burns et al. 2018 ; Gibbons et al. 2008 ; O’Neill et al., 2020a). By supporting a range of potential data end-users to comprehensively monitor ecological change, the EMSA aims to facilitate adaptive management across Australian landscapes. The shift to a systematic form of monitoring will also necessarily involve socio-cultural change across Australian NRM and ecological science communities. Importantly, those socio-cultural processes where people engage with the environment and with each other to generate and present data in a range of forms, create both opportunities and problems. Standardised monitoring has the potential to inform new approaches to environmental management, from investment in carbon sequestration and biodiversity conservation outcomes, to hazard management, to an increased transparency of Australian ecology that would increasingly allow the public to follow outcomes from management (Voss et al., 2009 ; Meadowcraft and Steurer, 2018). Although implementing such an approach may be broadly viewed as worthwhile, previous research suggests that if there are significant socio-cultural difficulties with implementation, required improvements in ecological knowledge will be unsuccessful (Biber, 2013 ; Sanchirico et al., 2014 ; Michener, 2015 ). For that reason, as the monitoring transition is implemented across Australia, it is important to examine how stakeholders perceive and interact with the systemic change to guide the transition and avoid conflict. This research aims to gauge the perceptions of a preliminary sub-set of Australian ecological monitoring stakeholders in order to identify and begin to understand the socio-cultural challenges to EMSA implementation. How these challenges can be addressed will be key to ensuring successful implementation of the protocols. While this article identifies key stakeholder perceptions of and gaps in understanding related to standardised ecological monitoring, it also makes suggestions on how the approach could help to inform an emerging new era in environmental management in Australia. We initially introduce the new systematic ecological monitoring system to outline the context of the research. Subsequently, the socio-cultural aspects of ecological monitoring are described and an argument for improving understanding of those processes presented. We go on to describe the qualitative method used to gather data from key stakeholders across Australia. Key claims emerging from stakeholder narratives on the opportunities and risks are warranted with quotations from interviews and focus group discussions. Finally, we discuss the importance of generating mutual socio-ecological understanding for the success of future monitoring programs. 2. The Ecological Monitoring System Australia (EMSA) In 2021 the Terrestrial Ecosystem Research Network (TERN) partnered with the Australian Department of Climate Change, Energy, Environment and Water (DCCEEW) to design and standardise ecological monitoring and data systems for improved decision-making related to National Landcare Program (NLP) investments into NRM (O’Neill et al., 2020a; O’Neill et al., 2020b; DCCEEW, 2024a). The three-year project developed standardised field survey protocols to assist professionals such as NRM staff, managers and environmental consultants, as well as community volunteers to collect consistent and comparable monitoring data from different sites and ecosystems. Additionally, TERN and DCCEEW developed a data collection app, an associated data exchange system and data management standards. Together, these protocols, system and standards form EMSA. Such standardised environmental monitoring protocols and associated systems have not been used previously for Federal Government-funded NRM initiatives, so the new approach raises important questions about integration with NRM practices and socio-cultural norms for stakeholders across local, regional and national scales. Altogether, 24 EMSA protocols were developed that built on previous data aggregation systems and extensively tested field survey protocols, underpinned by the FAIR guiding principles for data sharing (O’Neill et al., 2020a; O’Neill et al., 2020b). The FAIR principles, established by a range of stakeholders in scientific data collection, are a set of measurable values intended to ‘enhance the reusability of data’ (Wilkinson et al., 2016). The four foundational principles are Findability, Accessibility, Interoperability, and Reusability that aim to facilitate data ‘deposition, exploration, sharing and reuse’, with the primary goal of access and reusability to support decision-making (Wilkinson et al., 2016; Devaraju et al., 2021 ; FORCE11, 2021). The principles outline an idealistic framework, but do not provide a strict methodology for achieving outcomes (Wilkinson et al., 2019 ). Data collection through EMSA will be facilitated by a custom-developed digital application named ‘ Monitor ’ (TERN, 2024 ). Monitor will operate on mobile devices that NRM practitioners take into the field to record observations and measurements. Data entries are constrained to a format that is designed to be immediately scientifically useful, such that Monitor does not allow for the entry of free text sentences that might introduce ambiguity. Instead, standardised drop-down lists are used, or specific numbers, counts or measures are entered. The data will be uploaded to the Australian Government’s Biodiversity Data Repository (BDR), according to the Australian Biodiversity Information Standard (ABIS), and the ecological data will be made available to end-users (DCCEEW, 2024b). Together, the transition in the monitoring approach does not only involve technological and scientific change, but also a socio-cultural shift for the monitoring community. For that reason, a widespread understanding and acceptance of EMSA by stakeholders will be key to its successful implementation. 3. Socio-cultural aspects of ecological monitoring The implementation of data standardisation is emerging as an important social issue in environmental management (Biber, 2013 ; Sanchirico et al., 2014 ; Michener, 2015 ). Monitoring is continually being conducted, and data interpreted and utilised by many different stakeholders whose varying interests and objectives inevitably influence their data needs. Like all social processes, attitudes of and approaches towards ecological monitoring differ between individuals and groups. As Norgaard ( 1992 , p. 95) noted, “Environmental science as a social process entails scientists entering into discourse, debating and rethinking each other’s understandings, and approaching an interpretive consensus.” Normative environmental science alone is failing to generate simple, universally agreed solutions to complex problems. The alternative is to acknowledge that the perceptions and behaviours of key research and management actors must be understood to generate knowledge to effectively implement environmental management approaches driven by science (Wittmayer and Schäpke, 2014 ). Without such social knowledge to inform a new ecological monitoring consensus, conflicts will be generated or maintained that could prevent the effective application of the systematic approach. The contemporary need for improved ecological monitoring is partly generated by an evolution in the reasons why more effective knowledge of environmental change is now required. At a local level, standardised methods will help NRM project managers report consistently on outcomes from their interventions. Beyond such important local goals, consistent data at a national scale enables governments and private interests to better evaluate and compare projects and target funding towards more successful management approaches. Such data have been lacking in Australia, with NRM projects and practitioners often operating independently using methods that are not always comparable or sufficient to inform good environmental science or decision-making (Field et al., 2007 ; van Dijk et al., 2014 ; Scheele et al., 2019 ) Important reviews such as the State of the Environment (DCCEEW, 2023a), the Threatened Species Action Plan (DCCEEW, 2023b) or Australia’s reporting on greenhouse gas emissions (DCCEEW, 2023c) can lack detail or accuracy without the ability to compare data seamlessly across jurisdictions, which will now be enhanced by systematic monitoring and the BDR. Alongside such immediate opportunities, a new era of risk is generating new data demands on Australian environmental management that will need readily available high-quality data to understand and apply across landscapes (Bardsley and Knierim, 2020 ). The world is experiencing increasing rates of climate change and biodiversity loss (IPBES, 2019; IPCC, 2022 ). As society is directly implicated in generating the global ecological crisis, the conservation community is interested in working with communities to implement adaptive management and evidence-based conservation approaches (Bennett, 2016 ; Schmidt-Traub et al., 2017 ). In response, new commercial and policy frameworks are being developed, such as the Australian Nature Positive Plan (DCCEEW, 2022), the Nature Repair Market (DCCEEW, 2024c), and the Agricultural Sustainability Framework (McRobert et al., 2023 ), in association with new opportunities for establishing national environmental standards, conservation planning, carbon sequestration and nature repair markets, which allow landholders to engage more holistically in regenerative landscape management (Laine et al., 2021 ; O’Donoghue et al., 2022 ; DCCEEW, 2024c). While it is envisioned that EMSA will primarily be used for Federal Government-funded NRM initiatives, broader use of the system by businesses, non-government organisations (NGOs) and other groups conducting terrestrial monitoring and research in Australia is anticipated, to generate a more comprehensive national ecological dataset. Together, the new approach to monitoring has the potential to guide improved monitoring and assessment across natural and anthropogenic landscapes, for sophisticated ecological analysis that allows for detailed management outcomes that are unique to place and system (Cleverly et al., 2019 ; Zurell et al., 2020 , Perry et al., 2023 ). The emerging practice of holistic ecological monitoring is tied to a growing awareness of the importance of better knowledge of environmental conditions, as well as social and economic prosperity, to advance sustainable development (Jaegar et al., 2008; Ferrario et al., 2022). Holistic environmental monitoring aims to develop a comprehensive representation of a landscape integrated in its wider ecological context (Ferrario et al., 2022). The concept of adaptive co-management acknowledges the importance of social networks and norms between stakeholders for improved collaboration to manage systems to respond to disturbances and adapt to change (Armitage, 2005 ; Cundill and Fabricius, 2009 ; Bardsley et al., 2021 ). Adaptive co-management emphasises learning-by-doing through monitoring and action (Walters and Holling, 1990 ; Daniels and Walker, 2001 ), with a focus on collaborative and inclusive decision-making (Borrini-Feyerabend, 1996 ; Carlsson and Berkes, 2005 ). Reflexivity and social learning as developed in the context of environmental management are conceptually related to adaptive co-management and particularly important for social aspects of a transition in an NRM approach. Reflexivity refers to an individual or group's ability to examine themselves in relation to their actions and interactions with others (Pienkowski et al. 2023 ). Social learning has been defined as a process of learning through collective, iterative reflection (Keen et al., 2005; Fernandez-Gimenez et al., 2008 ) or a learning outcome, such as a change in conceptions or attitudes, which becomes social learning when it is diffused through a larger network via social interaction (Reed et al., 2010). Gauging stakeholders’ awareness and practice of, or enthusiasm for measures resembling holistic monitoring and adaptive co-management will assist in determining how systematic monitoring in Australia may be further developed to ensure adaptive, evidence-based policy. In other words, without knowledge of the social processes that will enable change in monitoring, Australians and international stakeholders could struggle to understand change within the nation’s ecological systems or develop the adaptive capacity to manage future ecosystems. Issues in ecological monitoring within socio-ecological systems can be harder to manage than those within natural systems, as the former rely upon strategic behaviours of stakeholders and there are often limitations to controlled experimentation in anthropogenic systems (Sabatier, 1995 ). Therefore, scientists are increasingly being called to embrace multidisciplinary approaches, including social science research, to better understand and resolve socio-cultural challenges to effective environmental management and monitoring (Ferrario et al., 2022). Significant portions of the relevant literature on social processes influencing monitoring specifically discuss ‘community monitoring’ or monitoring via ‘citizen science’ programs (e.g. Wiseman and Bardsley, 2016 ; Danielsen et al., 2022 ; Bonney et al., 2023 ; Alblas and van Zeben, 2023 ). Methods of monitoring with community participation are often diverse in how they employ local, traditional and scientific knowledge, which can undermine the integrity of the data generated (Danielsen et al., 2009 ; 2022 ). For example, community-based monitoring in Australia’s rangeland environments is constrained by sparse human populations across large areas and by resource-limited regional bodies that are distanced from centres of economic and political power (Reynolds et al., 2007 ; White et al., 2012 ). These disadvantages are concentrated within remote Indigenous communities due to political, socio-economic, and cultural marginalisation within Australian society (Davies et al., 2008 ; AW NRM Board, 2013). There is impetus for Australia to better integrate Indigenous community-based monitoring into regional environmental management (Wiseman and Bardsley, 2016 ; Thompson et al., 2020 ). Systems such as EMSA could help to improve the effectiveness of holistic community-based monitoring by standardising approaches to data collection, management and sharing, thereby improving processes and outcomes even for individuals or groups in remote locations. Beyond such an aim, too little is understood of professional actors’ perceptions of decision-making, enactment and analysis regarding ecological monitoring. By examining how those professionals perceive the transition to a standardised national approach to ecological monitoring, we can explore the socio-cultural framing of monitoring to generate knowledge on why and how it could best be implemented. 3.1. Achieving social change for successful ecological monitoring standardisation Social tensions in association with monitoring programs can undermine environmental management success. Such social conflict may be particularly difficult to resolve because scientists tend to focus on data and hypotheses, and can underestimate other values key to the social processes of environmental monitoring and management (Sabatier and Jenkins-Smith, 1993 ; Doremus, 2007 ). In response, there are a range of methods emerging for overcoming social conflict during technical transitions and facilitating successful monitoring outcomes. The importance of education for overcoming socio-cultural barriers to ecological monitoring standardisation is now well established. If stakeholders hold entrenched negative perceptions of an approach for reasons that lack strong evidence, education can fill gaps in understanding (Sharma and Monterio, 2016). NRM service providers have identified that they are open to adopting a standard method if they can see the value of the approach (Cox, 2021 ). Indeed, previous research suggests that the better participants understand the objectives and value of a program, the more closely they will follow procedures accurately (Gitzen et al., 2012 ; Biber, 2013 ). For example, flexibility is allowed within EMSA to record information beyond that data which is strictly required by the protocols, which will be important both for maintaining participant interest and guiding evolution of the monitoring approach over time. It has been recommended that service providers be supported through education and stewardship programs that demonstrate the intrinsic value of a standardised methodology (Cox, 2021 ). In fact, part of the goal of this research is to inform training to accompany EMSA implementation. Another method of overcoming socio-cultural challenges to effective monitoring is through the development of mutual understanding to enable collaboration among stakeholders (Allen et al., 2011 ; Biber, 2013 ; Johannsson et al., 2022). Many successful long-term monitoring studies are built on partnerships between people with differing but complementary skills, including those concerned with the human dimensions of ecological monitoring, such as policy-makers (Danielsen et al., 2009 ; Lindenmayer et al., 2012 ; Ferrario et al., 2022). Such a transdisciplinary approach increases the relevance and impact of long-term ecological monitoring (Lynch et al., 2015 ). While improved communication between stakeholder groups may be sufficient for addressing low-level disagreements (Sanchirico et al., 2014 ), collaborative monitoring, where conscious information seeking is followed by shared critical analysis, has been found to promote learning and consensus building to inform NRM decisions (Cundill and Fabricius, 2009 ). Increasingly, such collaboration is expanding to include professionals beyond science, whose work involves the socio-cultural aspects of monitoring, such as social scientists, economists, and artists (e.g. Robin et al., 2010 ; Sanchirico et al., 2014 ). Opportunities for scientists, managers, industrial and public stakeholders to meet and exchange experiences and expectations can facilitate multidisciplinary monitoring projects. By investigating stakeholders’ experiences of collaboration with DCCEEW during the development of EMSA, this research also initiates a process of informing future opportunities for such collaboration. 4. Methods 4.1. TERN focus groups A qualitative approach was undertaken to review perceptions of the introduction of the EMSA protocols amongst NRM practitioners and other key stakeholders (Grypma et al., 2023 ). Two preliminary focus groups were conducted with TERN staff involved in developing EMSA, to discern any socio-cultural challenges they anticipate or have encountered while engaging other stakeholders during the protocol development process. The first focus group involved five EMSA staff who were involved in a project support officer capacity, and the second involved two staff who were primarily involved in project management and communications. Each focus group ran for approximately one hour and twenty minutes. Focus groups are regularly used to evaluate program and policy implementation (Ryan et al., 2014 ). Asking stakeholders, through a focus group, to identify potential barriers to program implementation before a program has started is an effective method of rapidly informing program implementation at minimal cost (Gilmartin et al., 2019 ). Focus groups are also a valuable starting point to investigate the socio-technical context in which TERN operates. The discussions provided initial context and depth of understanding regarding stakeholders’ thoughts and experiences pertaining to EMSA (Ryan et al., 2014 ). Therefore, the focus groups assisted in planning the stakeholder interviews by providing key points of consideration for interviews. Participants were emailed the list of discussion questions a week prior to their session and were invited to individually note their responses to the questions in their own time. The three pre-prepared questions most relevant to socio-cultural challenges to EMSA implementation then guided the group discussions. Notes taken during the focus group focussed on the participants’ verbal responses and prompted follow-up questions, while audio recorded and transcribed data ensured quotes were accurately captured. 4.2. Semi-structured interviews The majority of primary data for this study was collected through twenty semi-structured interviews. Interviews were conducted with a diverse range of stakeholders who have, or will soon be, engaging with EMSA in their work. This included those involved in developing and managing EMSA, those who will be involved in collecting data through protocol implementation, and those involved in using the resultant data via the BDR. Specifically, participants included ecologists from both government agencies and academia, NRM staff involved in project design and reporting, and DCCEEW Nature Positive Integration division staff [See Table 1 ]. Together with the focus group data, the interviews highlight the wide range of perceptions that exist in relation to standardised ecological monitoring in Australia. This study is unique in its examination of the perceptions of ecological monitoring standards and system developers, data collectors and end-users in conjunction (Cf. Alblas and van Zeben, 2023 ; Chase and Levine, 2018). This feature allows for comparison of the observations and opinions of these cohorts, enabling the development of a holistic picture of the socio-cultural processes of standardising ecological monitoring in Australia. Interviews ranged in length from forty-five to ninety minutes and were conducted either Face-to-Face or via Zoom. In the pursuit of anonymity, interviewees are referred to by general descriptors of their roles [See Table 4.1]. It was important to differentiate the participants in this manner in order to compare and distinguish responses by background. ‘NRM coordinator’ refers to a person who works as a conduit or facilitator of knowledge sharing between EMSA stakeholder groups such as NRM regions, state and commonwealth government agencies. ‘End-user’ refers to a representative of an organisation that will make use of the ecological monitoring data produced by EMSA. This method of participant anonymity was designed in accordance with the National Statement on Ethical Conduct in Human Research and approved by the University of Adelaide Human Research Ethics Committee (approval number H-2023-126). 4.2.1. Interview participant selection The small sample size of the focus groups and interviews does not intend to be socially representative or comprehensive. Rather, the sample was stratified to obtain responses from a range of key stakeholders to generate textured, in-depth findings through discussions with a variety of stakeholders. First, the researchers compiled a list of potential participants in association with the NRM Regions Australia Knowledge Broker to ensure a variety of stakeholders of different backgrounds and at different levels of their organisation were interviewed. The method is consistent with statistically non-representative stratified sampling, as variables were defined based on a hypothesis that those of different backgrounds will encounter or generate different socio-cultural challenges to EMSA implementation (Trost, 1986 ). Variables included stakeholder organisation (e.g. government or NRM service provider), region of Australia working within, and nature of engagement with EMSA (e.g. as a developer, data collector or end-user) [See Table 1 ]. Table 1 Semi-structured interviews: EMSA stakeholders Type of stakeholder Number of interviews conducted NRM region professional 10 consisting of: ● 2 with Tasmanian regions, ● 3 with South Australian regions, ● 2 with New South Wales regions, ● 1 with a Western Australian region, ● 1 with a Victorian region, and ● 1 with a Queensland region. DCCEEW EMSA professional 5 NRM coordinator 2 End-user 2 Academic researcher 1 4.3. Thematic analysis To ascertain and interpret key perceptions and socio-cultural challenges to EMSA implementation based on the focus groups and interviews conducted, the data was analysed using techniques of thematic analysis, as set out by Braun and Clarke ( 2021 ). Following transcription, the focus group data, including individual participant written responses, and each interview was read through and initial analytic insights noted. This familiarised the researchers with the entire dataset. Subsequently, the process of generating and elaborating concepts was commenced using the interpretative, inductive techniques of coding. Coding was both semantic (capturing the explicit or surface meaning) and latent (capturing more conceptual or implicit meaning) (Braun and Clarke, 2021 ). Consistency and accuracy of coding was achieved and the intrusion of bias limited, through application of the techniques of constant comparison and questioning (Corbin and Strauss, 2015 ; Glaser and Strauss, 1967 ). Constant comparison involves examining data both within and between documents (i.e. transcripts) to group together data that are conceptually similar. Questioning involves asking various questions of the data in order to draw meaning from them. Typical questions included, ‘What are the issues, problems, and concerns here?’, ‘Who are the actors involved?’ and ‘How do they define the situation?’. Following an informal coding process, concepts were integrated where appropriate and grouped into broader themes and key messages. We summarise the key findings from the qualitative data using tables, and elaborate on key themes with evidence warranted from the qualitative data following the approach taken by Bardsley et al. ( 2023 ). 5. Results This section presents the key findings from the focus groups and interviews. The thematic analysis revealed a range of perceived potential advantages of EMSA [Table 2], but in the analysis below we emphasise the perceived socio-cultural challenges relating to EMSA and its implementation [Table 3]. Advantage of EMSA mentioned Respondent NRM region professionals DCCEEW EMSA professionals NRM knowledge brokers End-users Academic TERN focus groups Total 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Enable/validate national ecological research x x x x x x x x x x x x x x x x x 17/21 High quality national level information x x x x x x x x x x x x x x x x x 17/21 Accountability for public funding x x x x x x x x x x x x x x 14/21 Reliable collection and storage of data x x x x x x x x x x x x x 13/21 Guide reporting (e.g. SOE, international) x x x x x x x x x x x x 12/21 Enable reproducible science-based monitoring x x x x x x x x x x x 11/21 Enable longevity of ecological monitoring x x x x x x x x x 9/21 Easily accessible data x x x x x x x x 8/21 Flexible systems that adapt to needs x x x x x x x x 8/21 Create efficiencies in data collection/ management/ use x x x x x x x x 8/21 Normalisation of national-scale monitoring x x x x x x 6/21 Enable investment in ecological outcomes x x x x x x 6/21 Table 2. Key advantages of EMSA perceived by stakeholders Table 3. Key socio-cultural challenges of EMSA perceived by stakeholders Sociocultural challenge mentioned Respondent NRM region professionals DCCEEW EMSA professionals NRM knowledge brokers End-users Academic TERN focus groups Total 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 Insufficient capacity to implement protocols x x x x x x x x x x x x x x x x x x x x x 21/21 Data utility and access for regional projects x x x x x x x x x x x x x x x x x x 18/21 Adaptability of EMSA protocols/tools/system x x x x x x x x x x x x x x x x x x 18/21 Communications regarding EMSA roll-out x x x x x x x x x x x x x x x 15/21 Attachment to current practices x x x x x x x x x x x x x x x 15/21 Demonstration of clear EMSA purpose/value x x x x x x x x x x x x x 13/21 Giving and responding to feedback x x x x x x x x x x x x 12/21 Weaken local relationships and knowledge x x x x x x x x x x x 11/21 Need to see short-term advantages x x x x x x x x x x x 11/21 Commonwealth/State government coordination x x x x x x x x x x 10/21 Initial EMSA development consultation x x x x x x x x x x 10/21 Autonomy of NRM regions x x x x x x x 7/21 5.1. Insufficient capacity to carry out EMSA protocols Respondents noted that natural resource management, and ecological monitoring in particular, is not well resourced. All respondents raised the issue of adequate financial and labour resources being required to facilitate the transition to systematic monitoring, especially in regional and remote areas. Some highlighted that the potential for a lack of financial support was their primary concern regarding EMSA protocol implementation. Our biggest concern is that we can't implement [the EMSA protocols] because we're not resourced to implement them. They will add considerably to the cost of our operations, and if that [cost] has to come out of projects, we might say “We won't achieve these outcomes on the ground, and [instead] we'll spend [funds] on monitoring the limited outcomes that we've achieved.” (NRM region professional 4) Part of that concern originates from the recent shift in the way NRM activities are funded by the Commonwealth Government from a grant-based funding model to a procurement model, which largely assigns NRM regions with the role of a service provider (Rolfe et al., 2017 ). Respondents noted that this method of funding gives the Commonwealth more power to demand particular outcomes, which regions may struggle to apply. NRM funding cycles run over short time periods and do not sufficiently cover many key management operations over the longer term. Stakeholders were concerned that EMSA implementation would generate additional bureaucratic burdens limiting time to develop understanding of local issues or implementing appropriate management interventions. The realistic impact that you can have in five years with the dollars provided is sometimes quite limited. Sometimes partnerships and engagement are the main outcome… For example, you’ve managed to get a memorandum of understanding with a traditional owner group… [in that case] you're not paying for an environmental outcome, and you need to be clear, “In the next five years, we're just scratching the surface of trying to fix this problem.” The TERN protocols are [irrelevant] in that situation. (NRM region professional 3) How difficult is it to establish relationships with businesses, land councils and enterprises in remote regions, from Canberra, over a 4 to 5 year period? And then pull funding, or know funding is going to end, or maybe keep going into the next programme… (DCCEEW EMSA professional 15) 5.1.1. Data utility and access for regional projects Data is used all the time by local and regional environmental management groups to review outcomes of environmental management interventions and make decisions for future actions. A widespread concern emphasised by NRM region professionals was that data gathered utilising the EMSA protocols and associated tools would not reveal whether their local projects, including Commonwealth funded activities, are producing desired outcomes. What the Commonwealth tends to revert to is measuring biodiversity the same way everywhere, at a national level. You get this complete incongruence with what they're investing in, which is very local, and what they're measuring… that means they run into problems. I think there's also a social element: you're engaging regional boards, staff and communities in a process which is very local to them, and then you're asking them to engage in this evaluation process, which has nothing to do with them. Essentially, you're asking them to go out and measure things which, from their perspective, have no bearing on whether they're being effective or not. (NRM Coordinator 17) Another widespread concern was that EMSA data would not be readily available in a form that they could use to easily make decisions or verify actions. While the protocols are organised to provide baseline data that could answer a range of ecological questions, such scientific analysis could be difficult to implement at regional scales. In fact, several respondents argued that the best outcomes came when high quality monitoring could be undertaken locally with limited external interference. We haven't been given any indication how we get our data back. We know we have to enter data into the app, and it goes into the Biodiversity Data Repository, but there is no indication of how we get it back, and no indication of what we do with it then, because if you have one plot with thousands of individual data points in it; that's beyond the capacity of a lot of NRMs to analyse. (NRM region professional 2) 5.1.2. Adaptability of EMSA protocols, tools and system Finally, the collection, storage and utilisation of high-quality ecological data was the other major theme raised by more than 85% of participants. They emphasised that the EMSA protocols, tools and systems need to be made adaptable to suit unique ecological circumstances, with the capacity to evolve as implementation commences and technical or logistical issues are identified. I think [the protocols] are pretty flexible, but plot size will be a primary limiting factor, and [ensuring the protocols can be used with] different plot sizes is something that we're going to explore. There will be heaps of situations where you need to adjust plot size, and at the moment there isn't flexibility to do that, but a lot of the protocols are fairly broad. They have been designed to be applicable to different systems. There may be a period of figuring out how things need to be changed or adapted to capture everything. (TERN focus groups) 5.2. Communication, collaboration and education In a third set of questions, we asked respondents to elaborate on approaches they were suggesting to support EMSA implementation. Most responses linked to the most important issues highlighted above, with ideas for either better exploitation of opportunities from systematic ecological monitoring, or avoidance of potential negative impacts or constraints. 5.2.1. Opportunities to give feedback and receive responses About half of respondents acknowledged giving and responding to feedback as an important social process to engage in during EMSA implementation. While opportunities for communication had been made available to regional stakeholders, they felt there was insufficient acknowledgement or incorporation of that feedback into co-design of the protocols or monitoring approach. This may have negatively influenced perceptions of EMSA early on and made some regional NRM professionals sceptical of the worth of further engagement with the process. It didn't feel like genuine consultation. There was no in-depth consultation, particularly on what NRM needs are, and how it would actually work… There was a spreadsheet sent out for feedback. I asked nine questions, and nothing happened… I chased it up: “I haven't gotten any answers.” I've since received answers to four of my questions… This [interview] is the first proper opportunity I've had to provide any feedback to the department. (NRM region professional 2) There is a communication challenge to explain complex scientific decisions that aim to meet universal goals on a general scale that will respond to all regional concerns. For example, some feedback ideas on draft protocols could not be appropriately integrated into the approach, but this might not have been effectively communicated to regional groups. Throughout the whole project, we've repeatedly told [NRM service providers] what we're doing. We've asked them for feedback. We've gotten very little feedback, and the feedback we have gotten hasn't been of any use anyway. That's probably why we haven't engaged as much as we probably should have. (TERN focus groups) Therefore, A key narrative was that a major transition in a scientific approach would benefit from regular communication and greater direct participation from key stakeholders to ensure changes are understood and to facilitate ownership of new technical processes. In fact, several stakeholders argued that NRM service providers should have been far more directly involved in the initial phase of crafting a solution to the problem of inadequate ecological monitoring. I don't feel the NRM sector was at all involved in the discussion of how we can make things better. Before going to TERN and saying “Solve this problem for us”, have this conversation with the regions. They've got us out there in the regions that they're contracting projects with, we know better than anyone about the implementation side, and I feel like we weren't consulted at all. (NRM region professional 6) Authentic engagement with NRM stakeholders will be important as EMSA implementation continues. One idea suggested by numerous respondents was the importance of multimodal training in EMSA to assist in building relationships and confidence in the new system. When the [state-based] vegetation benchmarks project was rolled out…we went through a 2.5-year training process - the focus was on training left, right and centre to target as many people as possible - and we're still trying to encourage the uptake of that methodology. (NRM region professional 4) Some volunteer groups, such as citizen scientists, may be more reluctant to apply the protocols and use the app and related systems. One suggestion was for further face-to-face engagement with NRM sub-regional partners, who in turn could become change-leaders within their region. Some regions or groups with less capacity or unique monitoring needs may need targeted direct training and on-going assistance to effectively integrate the protocols into their monitoring systems. I think having champions associated with [EMSA] is really important. There are a lot of events that happen in the bush, where you can just book an hour to be face-to-face with people. There's nothing better. Once you get key people on side, then the ideas will spread and be taken up. (Academic) Although it was beyond the scope of the initial phase of EMSA development, the co-design of regional projects was also seen as a highly valuable tool for successful implementation in the future. The negotiation of projects in association with monitoring, and the choice of application of particular protocols suited to local needs would be a vital step in the acceptance of the new monitoring approach. I’d like to see more intensive engagement with us as delivery partners for this type of work. We [could] assess the protocols and their applicability [together with DCCEEW]. I hope there’s a fair bit of opportunity to opt-out where we can justify why we're not following those protocols. Because some of the work we do is simply community engagement. It's not about collecting rigorous monitoring data. (NRM region professional 5) 6. Discussion This study demonstrates how an array of complex social, institutional, and ecological issues, operating at various scales, emerge from a change in scientific approach within a community. Acknowledgement of the diversity of experiences of monitoring standardisation within the NRM community is a first step in resolving that complexity. Complex systems require a multivariate, integrated approach to environmental management (Bellamy et al., 2001 ; Cundill and Fabricius, 2008), and governance approaches like adaptive co-management have come about as a means of dealing with such complexity and uncertainty (Ollson et al., 2004). These approaches rely on collaboration among a diverse set of actors, and on social coordination whereby actions are coordinated by stakeholders in a self-organising and self-enforcing manner. Stakeholders requested more autonomy and flexibility throughout our research, so their involvement in how the protocols evolve would enable NRM practitioners to coordinate associated actions and self-organise to facilitate appropriate regional methods for monitoring standardisation. Our findings indicate that reflexivity is a vital concept to address the complexity involved in standardisation of ecological monitoring. New approaches to environmental management will increasingly have to account for the complexity of socio-ecological systems in order to overcome the unprecedented challenges that will arise in the wake of future global change. While both informal and institutionalised reflexivity require allocation of limited time and resources, when intentionally undertaken, reflexive processes can be integrated into adaptive management at multiple points, helping environmental management stakeholders better reach their goals (Mol, 1996 ; Pearson and Bardsley, 2022 ; Pienkowski et al., 2023 ). Reflexivity plays a transformative role, supporting practitioners to learn to regularly reevaluate their goals and methods to meet changing needs. Although the term was not mentioned, the participants in this study expressed a deep understanding of and desire for reflexive approaches to monitoring standardisation. EMSA itself is the outcome of a comprehensive re-evaluation of Australian ecological monitoring and reporting, and the need for standardisation was endorsed as a response to the shortfalls of current monitoring practice. The major concerns of protocol adaptability, consequent data utility, lack of consultation and adequate opportunities to give feedback conveyed by NRM stakeholders are essentially concerns of a lack of reflexivity to date within EMSA implementation. The lack of resourcing of Australian NRM in general, and concerns with insufficient extra support for this ‘upgrade’ of ecological monitoring in Australia, emerged as the key narrative. As learning and re-evaluation takes time, reflexive approaches are more expensive than simple knowledge transfer systems. Importantly, our results show that capacity limitations are not only about funding, but also relate to an NRM organisation’s ability to take the time to engage in, and benefit from, collaboration and learning activities. Aside from providing more funding, making social learning an explicit objective of the change process is necessary to build social capacities (Fernández-Giménez et al., 2019 ; Dimmock et al., 2014 ; LoSchiavo et al., 2013 ). Therefore, resourcing for EMSA implementation needs to not only update tools and technical activities, but also facilitate learning processes to generate the social licence for the new monitoring system. Our results support this conclusion, with respondents calling for multimodal training, the development of local champions to spearhead implementation, and co-design of projects utilising the protocols. Improved communication between researchers and applied sectors has been proposed as a practical step towards enhancing collaboration for adaptive environmental management (Brownson and Fowler, 2020 ; Allan and Watts, 2017; Hagell and Ribic, 2014 ). When researchers work closely with science end-users, constructive change is enabled because collaboration can immediately and directly address social obstacles. Trust building, dialogue and active involvement have been identified as among the most recognised qualities of collaboration (Fiest et al., 2020). Respondents’ concerns about a perceived lack of genuine consultation and acknowledgement of feedback, reveal the importance of clear communication at all stages of an environmental management project that aims to standardise and streamline practices. As Månsson et al. (2023) also argue, by developing understanding of the socio-cultural challenges to the implementation of a new environmental management approach, our research demonstrates the advantages of such transdisciplinary learning to inform the standardisation of ecological monitoring. 7. Conclusion Environmental management stakeholders are not opposing the standardisation of ecological monitoring. However, as a unifying approach to monitoring data is applied, differentiated methods and approaches to suit local contextual situations and desired outcomes are crucial to successful implementation. Reflexivity is already starting to be built into EMSA implementation through opportunities for project co-design and protocol opt-out, but there are also key social processes beyond these mechanisms related to the transition that will need to be developed in the future. There are both important academic and practical values in undertaking research to analyse how transitions in ecological monitoring will be accepted by scientific and NRM communities. Social knowledge on how best to implement technological and procedural change will be vital to inform a new era in environmental management: an era that will increasingly incorporate environmental change; green investment; regeneration of multifunctional landscapes; increasing natural hazard risk; and a broad range of new relationships between people and their ecology. In this case, the normalisation of high-quality national level ecological monitoring to achieve an improvement in the understanding of the national environment, and increased accountability of funding for public investment were the most widespread perceived advantages. The most commonly perceived socio-cultural challenges centred around the adaptability of EMSA methodologies for NRM service providers, and the need for adequate resourcing and prioritisation of relationships with stakeholders. To respond to such socio-ecological complexity, strong participatory approaches will be needed to develop effective technical solutions. In fact, it is possible to argue that mutual social learning between scientists and practitioners that can enable ownership of the new approach and lead to co-design of policy and practice must be normalised to guide effective transitions in environmental management. Declarations Acknowledgements This research is part of a body of work funded by the Australian Government Department of Climate Change, Energy, the Environment and Water (DCCEEW). TERN is funded by the National Collaborative Research Infrastructure Strategy. This research was approved by the University of Adelaide Human Research Ethics Committee (approval number H-2023-126). 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Sanchirico, JN, Springborn, MR, Schwartz, MW & Doerr, AN 2014, ‘Investment and the Policy Process in Conservation Monitoring: Investment, Policy, and Conservation Monitoring’, Conservation Biology , vol. 28, no. 2, pp. 361–371. https://doi.org/10.1111/cobi.12187 Scheele, BC, Pasmans, F, Skerratt, LF, Berger, L, Martel, A, Beukema, W, Acevedo, AA, Burrowes, PA, Carvalho, T, Catenazzi, A, De la Riva, I, Fisher, MC, Flechas, SV, Foster, CN, Frías-Álvarez, P, Garner, TWJ, Gratwicke, B, Guayasamin, JM, Hirschfeld, M, Kolby, Jonathan E, Kosch, TA, La Marca, E, Lindenmayer, DB, Lips, KR Longo, AV, Maneyro, R, McDonald, CA, Mendelson, J, Palacios-Rodriguez, P, Parra-Olea, G, Richards-Zawacki, CL, Rödel, M, Rovito, SM, Soto-Azat, C, Toledo, LF, Voyles, J, Weldon, C, Whitfield, SM, Wilkinson, M, Zamudio, KR, Canessa, S 2019, ‘Amphibian fungal panzootic causes catastrophic and ongoing loss of biodiversity’, Science (American Association for the Advancement of Science), vol. 363, no. 6434, pp. 1459–1463. https://doi.org/10.1126/science.aav0379 Schmidt-Traub, G, Kroll, C, Teksoz, K, Durand-Delacre, D & Sachs, JD 2017, ‘National baselines for the Sustainable Development Goals assessed in the SDG Index and Dashboards’, Nature Geoscience, vol. 10, no. 8, pp. 547–555. https://doi.org/10.1038/ngeo2985 Sharma, R & Monteiro, S 2016, ‘Creating Social Change: The Ultimate Goal of Education for Sustainability’, International Journal of Social Science and Humanity , vol. 6, no. 1, pp. 72–76. https://doi.org/10.7763/IJSSH.2016.V6.621 Sparrow, BD, Edwards, W, Munroe, SEM, Wardle, GM, Guerin, GR, Bastin, JF, Morris, B, Christensen, R, Phinn S & Lowe, AJ 2020a, 'Effective ecosystem monitoring requires a multi-scaled approach', Biological Reviews of the Cambridge Philosophical Society , vol. 95, no. 6, pp. 1706-1719. https://doi.org/10.1111/brv.12636 Sparrow, BD, Foulkes, JN, Wardle, GM, Leitch, EJ, Caddy-Retalic, S, van Leeuwen, SJ, Tokmakoff, A, Thurgate NY, Guerin GR and Lowe, AJ 2020b, ‘A Vegetation and Soil Survey Method for Surveillance Monitoring of Rangeland Environments’, Frontiers in Ecology and Evolution, vol. 8. doi: 10.3389/fevo.2020.00157 TERN 2024, Ecological Monitoring System Australia (EMSA) , accessed 23/03/2024, https://www.tern.org.au/emsa-protocols-manual Thompson, KL, Lantz, TC & Ban, NC 2020, ‘A review of Indigenous knowledge and participation in environmental monitoring’, Ecology and Society , vol. 25, no. 2, pp. 10. https://doi.org/10.5751/ES-11503-250210 Trost, JE 1986, ‘Statistically nonrepresentative stratified sampling: A sampling technique for qualitative studies’, Qualitative Sociology , vol. 9, no. 1, pp. 54–57. https://doi.org/10.1007/BF00988249 van Dijk, A, Mount, R, Gibbons, P, Vardon, M & Canadell, P 2014, ‘Environmental reporting and accounting in Australia: Progress, prospects and research priorities’, The Science of the Total Environment , vol. 473–474, pp. 338–349. https://doi.org/10.1016/j.scitotenv.2013.12.053 Voss, J-P, Smith, A & Grin, J 2009, ‘Designing long-term policy: rethinking transition management’, Policy Sciences , vol. 42, no. 4, pp. 275–302. https://doi.org/10.1007/s11077-009-9103-5 Walters, CJ & Holling, CS 1990, ‘Large‐Scale Management Experiments and Learning by Doing’, Ecology , vol. 71, no. 6, pp. 2060–2068. https://doi.org/10.2307/1938620 White, A, Foulkes, JN, Sparrow, BD & Lowe, AJ 2012, ‘Biodiversity monitoring in the rangelands’ in D Lindemayer and P Gibbons (eds), Biodiversity Monitoring in Australia , CSIRO publishing, Canberra, pp. 179– 190. Wilkinson MD, Dumontier M, Aalbersberg IJ, Appleton G, Axton M, Baak A, Blomberg N, Boiten JW, da Silva Santos LB, Bourne PE, Bouwman J, Brookes AJ, Clark T, Crosas M, Dillo I, Dumon O, Edmunds S, Evelo CT, Finkers R, Gonzalez-Beltran A, Gray AJ, Groth P, Goble C, Grethe JS, Heringa J, t Hoen PA, Hooft R, Kuhn T, Kok R, Kok J, Lusher SJ, Martone ME, Mons A, Packer AL, Persson B, Rocca-Serra P, Roos M, van Schaik R, Sansone SA, Schultes E, Sengstag T, Slater T, Strawn G, Swertz MA, Thompson M, van der Lei J, van Mulligen E, Velterop, J Waagmeester, A Wittenburg P, Wolstencroft K, Zhao J & Mons, B 2016 'The FAIR Guiding Principles for scientific data management and stewardship', Scentific Data , vol. 3, no. 15, pp. 160018. https://doi.org/10.1038/sdata.2016.18 Wilkinson MD, Dumontier M, Sansone SA, Bonino da Silva Santos LO, Prieto M, Batista D, McQuilton P, Kuhn T, Rocca-Serra P, Crosas M & Schultes E 2019, ‘Evaluating FAIR maturity through a scalable, automated, community-governed framework’, Scientific Data , vol. 6, no. 174. https://doi.org/10.1038/s41597-019-0184-5 Wiseman, ND & Bardsley, DK 2016, ‘Monitoring to Learn, Learning to Monitor: A Critical Analysis of Opportunities for Indigenous Community-Based Monitoring of Environmental Change in Australian Rangelands’, Geographical Research , vol. 54, no. 1, pp. 52–71. https://doi.org/10.1111/1745-5871.12150 Wittmayer, JM and Schäpke, N, 2014, ‘Action, research and participation: roles of researchers in sustainability transitions’, Sustainability science , no. 9, pp. 483-496. https://doi.org/10.1007/s11625-014-0258-4 Zurell, D, Franklin, J, König, C, Bouchet, PJ, Dormann, CF, Elith, J, Fandos, G, Feng, X, Guillera‐Arroita, G, Guisan, A, Lahoz‐Monfort, JJ, Leitão, PJ, Park, DS, Peterson, AT, Rapacciuolo, G, Schmatz, DR, Schröder, B, Serra‐Diaz, JM, Thuiller, W, Yates, KL, Zimmermann, NE and Merow, C 2020, ‘A standard protocol for reporting species distribution models’, Ecography (Copenhagen) , vol. 43, no. 9, pp. 1261–1277. https://doi.org/10.1111/ecog.04960 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 26 Sep, 2024 Read the published version in Environmental Management → Version 1 posted Editorial decision: Revision requested 13 Jun, 2024 Reviews received at journal 13 Jun, 2024 Reviews received at journal 12 Jun, 2024 Reviews received at journal 07 Jun, 2024 Reviewers agreed at journal 17 May, 2024 Reviewers agreed at journal 17 May, 2024 Reviewers agreed at journal 16 May, 2024 Reviewers invited by journal 16 May, 2024 Editor assigned by journal 01 May, 2024 Submission checks completed at journal 29 Apr, 2024 First submitted to journal 28 Apr, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Bardsley","email":"","orcid":"","institution":"University of Adelaide","correspondingAuthor":false,"prefix":"","firstName":"Douglas","middleName":"K.","lastName":"Bardsley","suffix":""},{"id":297752679,"identity":"fd0d266c-dcad-49ab-90f8-d9af313703ad","order_by":2,"name":"Ben Sparrow","email":"","orcid":"","institution":"University of Adelaide","correspondingAuthor":false,"prefix":"","firstName":"Ben","middleName":"","lastName":"Sparrow","suffix":""}],"badges":[],"createdAt":"2024-04-28 11:10:20","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4337606/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4337606/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1007/s00267-024-02049-2","type":"published","date":"2024-09-26T15:56:52+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":65627777,"identity":"5d4c71e5-ae02-4b31-9e59-8e4c74dd6aae","added_by":"auto","created_at":"2024-09-30 16:16:29","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":922275,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4337606/v1/e9815058-7fa4-4030-8dba-cf1e69b8a2f4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The critical social processes for standardising the ecological monitoring of Australian landscapes","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe social aspects of ecological monitoring are often overlooked. Ecological monitoring provides vital information for decision-makers and natural resource management (NRM) practitioners to make informed environmental management decisions. Successful monitoring measures ecological change (by effectively providing baseline data) and informs a range of decisions, actions and research relevant to environmental management policy and practice (Burns et al., \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Monitoring methods need to quantify current ecological condition in a manner which enables the forecasting of ecosystem change to improve risk management and sustainable economic and social development (Lindenmayer et al., \u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Such monitoring continues to be funded and conducted, and the resultant data interpreted and utilised by stakeholders whose varying interests and objectives inevitably influence their work in different ways. Nonetheless, the implications of those social processes are under-represented in the literature.\u003c/p\u003e \u003cp\u003eFor a long time, ecological monitoring across Australia has utilised a wide variety of different ecological monitoring methodologies resulting in data that is difficult to analyse across place or time. Much of the ecological data that is currently generated is difficult to compare with other data or it has been collected using inappropriate methods for the intended aims (Likens and Lindenmayer, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Sparrow et al. 2020a; Sparrow et. al. 2020b). In response to these limitations, a new systematic approach to ecological monitoring has been developed as a collaboration between the Terrestrial Ecosystem Research Network (TERN) and the federal Department of Climate Change, Energy, the Environment and Water and has been called the Ecological Monitoring System Australia (EMSA). It is guided by specified ecological field survey modules, or protocols, and associated data systems, and aims to generate a national dataset to improve data collection, storage and access (TERN, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). While implementing such a transformation in scientific approach will require many technical adjustments, it is also essential that the social aspects of ecological monitoring are considered to ensure the uptake and adoption of these long-term monitoring programs. This article describes research undertaken to understand the key socio-cultural processes relevant to developing a systematic monitoring program for Australia.\u003c/p\u003e \u003cp\u003eNew challenges continue to emerge for Australian environmental, social and economic systems largely driven by environmental change. To understand this change, a new systematic monitoring system is being implemented across terrestrial landscapes to ensure that the resulting evolution in ecosystems can be understood by scientists, policy makers, and the general public (Burns et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Gibbons et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; O\u0026rsquo;Neill et al., 2020a). By supporting a range of potential data end-users to comprehensively monitor ecological change, the EMSA aims to facilitate adaptive management across Australian landscapes. The shift to a systematic form of monitoring will also necessarily involve socio-cultural change across Australian NRM and ecological science communities. Importantly, those socio-cultural processes where people engage with the environment and with each other to generate and present data in a range of forms, create both opportunities and problems. Standardised monitoring has the potential to inform new approaches to environmental management, from investment in carbon sequestration and biodiversity conservation outcomes, to hazard management, to an increased transparency of Australian ecology that would increasingly allow the public to follow outcomes from management (Voss et al., \u003cspan citationid=\"CR91\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Meadowcraft and Steurer, 2018). Although implementing such an approach may be broadly viewed as worthwhile, previous research suggests that if there are significant socio-cultural difficulties with implementation, required improvements in ecological knowledge will be unsuccessful (Biber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sanchirico et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Michener, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). For that reason, as the monitoring transition is implemented across Australia, it is important to examine how stakeholders perceive and interact with the systemic change to guide the transition and avoid conflict.\u003c/p\u003e \u003cp\u003eThis research aims to gauge the perceptions of a preliminary sub-set of Australian ecological monitoring stakeholders in order to identify and begin to understand the socio-cultural challenges to EMSA implementation. How these challenges can be addressed will be key to ensuring successful implementation of the protocols. While this article identifies key stakeholder perceptions of and gaps in understanding related to standardised ecological monitoring, it also makes suggestions on how the approach could help to inform an emerging new era in environmental management in Australia. We initially introduce the new systematic ecological monitoring system to outline the context of the research. Subsequently, the socio-cultural aspects of ecological monitoring are described and an argument for improving understanding of those processes presented. We go on to describe the qualitative method used to gather data from key stakeholders across Australia. Key claims emerging from stakeholder narratives on the opportunities and risks are warranted with quotations from interviews and focus group discussions. Finally, we discuss the importance of generating mutual socio-ecological understanding for the success of future monitoring programs.\u003c/p\u003e"},{"header":"2. The Ecological Monitoring System Australia (EMSA)","content":"\u003cp\u003eIn 2021 the Terrestrial Ecosystem Research Network (TERN) partnered with the Australian Department of Climate Change, Energy, Environment and Water (DCCEEW) to design and standardise ecological monitoring and data systems for improved decision-making related to National Landcare Program (NLP) investments into NRM (O\u0026rsquo;Neill et al., 2020a; O\u0026rsquo;Neill et al., 2020b; DCCEEW, 2024a). The three-year project developed standardised field survey protocols to assist professionals such as NRM staff, managers and environmental consultants, as well as community volunteers to collect consistent and comparable monitoring data from different sites and ecosystems. Additionally, TERN and DCCEEW developed a data collection app, an associated data exchange system and data management standards. Together, these protocols, system and standards form EMSA. Such standardised environmental monitoring protocols and associated systems have not been used previously for Federal Government-funded NRM initiatives, so the new approach raises important questions about integration with NRM practices and socio-cultural norms for stakeholders across local, regional and national scales.\u003c/p\u003e \u003cp\u003eAltogether, 24 EMSA protocols were developed that built on previous data aggregation systems and extensively tested field survey protocols, underpinned by the FAIR guiding principles for data sharing (O\u0026rsquo;Neill et al., 2020a; O\u0026rsquo;Neill et al., 2020b). The FAIR principles, established by a range of stakeholders in scientific data collection, are a set of measurable values intended to \u0026lsquo;enhance the reusability of data\u0026rsquo; (Wilkinson et al., 2016). The four foundational principles are Findability, Accessibility, Interoperability, and Reusability that aim to facilitate data \u0026lsquo;deposition, exploration, sharing and reuse\u0026rsquo;, with the primary goal of access and reusability to support decision-making (Wilkinson et al., 2016; Devaraju et al., \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; FORCE11, 2021). The principles outline an idealistic framework, but do not provide a strict methodology for achieving outcomes (Wilkinson et al., \u003cspan citationid=\"CR95\" class=\"CitationRef\"\u003e2019\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eData collection through EMSA will be facilitated by a custom-developed digital application named \u0026lsquo;\u003cem\u003eMonitor\u003c/em\u003e\u0026rsquo; (TERN, \u003cspan citationid=\"CR87\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). \u003cem\u003eMonitor\u003c/em\u003e will operate on mobile devices that NRM practitioners take into the field to record observations and measurements. Data entries are constrained to a format that is designed to be immediately scientifically useful, such that \u003cem\u003eMonitor\u003c/em\u003e does not allow for the entry of free text sentences that might introduce ambiguity. Instead, standardised drop-down lists are used, or specific numbers, counts or measures are entered. The data will be uploaded to the Australian Government\u0026rsquo;s Biodiversity Data Repository (BDR), according to the Australian Biodiversity Information Standard (ABIS), and the ecological data will be made available to end-users (DCCEEW, 2024b). Together, the transition in the monitoring approach does not only involve technological and scientific change, but also a socio-cultural shift for the monitoring community. For that reason, a widespread understanding and acceptance of EMSA by stakeholders will be key to its successful implementation.\u003c/p\u003e"},{"header":"3. Socio-cultural aspects of ecological monitoring","content":"\u003cp\u003eThe implementation of data standardisation is emerging as an important social issue in environmental management (Biber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Sanchirico et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Michener, \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Monitoring is continually being conducted, and data interpreted and utilised by many different stakeholders whose varying interests and objectives inevitably influence their data needs. Like all social processes, attitudes of and approaches towards ecological monitoring differ between individuals and groups. As Norgaard (\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e1992\u003c/span\u003e, p. 95) noted, \u0026ldquo;Environmental science as a social process entails scientists entering into discourse, debating and rethinking each other\u0026rsquo;s understandings, and approaching an interpretive consensus.\u0026rdquo; Normative environmental science alone is failing to generate simple, universally agreed solutions to complex problems. The alternative is to acknowledge that the perceptions and behaviours of key research and management actors must be understood to generate knowledge to effectively implement environmental management approaches driven by science (Wittmayer and Sch\u0026auml;pke, \u003cspan citationid=\"CR97\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Without such social knowledge to inform a new ecological monitoring consensus, conflicts will be generated or maintained that could prevent the effective application of the systematic approach.\u003c/p\u003e \u003cp\u003eThe contemporary need for improved ecological monitoring is partly generated by an evolution in the reasons why more effective knowledge of environmental change is now required. At a local level, standardised methods will help NRM project managers report consistently on outcomes from their interventions. Beyond such important local goals, consistent data at a national scale enables governments and private interests to better evaluate and compare projects and target funding towards more successful management approaches. Such data have been lacking in Australia, with NRM projects and practitioners often operating independently using methods that are not always comparable or sufficient to inform good environmental science or decision-making (Field et al., \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; van Dijk et al., \u003cspan citationid=\"CR90\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Scheele et al., \u003cspan citationid=\"CR82\" class=\"CitationRef\"\u003e2019\u003c/span\u003e) Important reviews such as the State of the Environment (DCCEEW, 2023a), the Threatened Species Action Plan (DCCEEW, 2023b) or Australia\u0026rsquo;s reporting on greenhouse gas emissions (DCCEEW, 2023c) can lack detail or accuracy without the ability to compare data seamlessly across jurisdictions, which will now be enhanced by systematic monitoring and the BDR. Alongside such immediate opportunities, a new era of risk is generating new data demands on Australian environmental management that will need readily available high-quality data to understand and apply across landscapes (Bardsley and Knierim, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2020\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe world is experiencing increasing rates of climate change and biodiversity loss (IPBES, 2019; IPCC, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As society is directly implicated in generating the global ecological crisis, the conservation community is interested in working with communities to implement adaptive management and evidence-based conservation approaches (Bennett, \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Schmidt-Traub et al., \u003cspan citationid=\"CR83\" class=\"CitationRef\"\u003e2017\u003c/span\u003e). In response, new commercial and policy frameworks are being developed, such as the Australian Nature Positive Plan (DCCEEW, 2022), the Nature Repair Market (DCCEEW, 2024c), and the Agricultural Sustainability Framework (McRobert et al., \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2023\u003c/span\u003e), in association with new opportunities for establishing national environmental standards, conservation planning, carbon sequestration and nature repair markets, which allow landholders to engage more holistically in regenerative landscape management (Laine et al., \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2021\u003c/span\u003e; O\u0026rsquo;Donoghue et al., \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; DCCEEW, 2024c). While it is envisioned that EMSA will primarily be used for Federal Government-funded NRM initiatives, broader use of the system by businesses, non-government organisations (NGOs) and other groups conducting terrestrial monitoring and research in Australia is anticipated, to generate a more comprehensive national ecological dataset. Together, the new approach to monitoring has the potential to guide improved monitoring and assessment across natural and anthropogenic landscapes, for sophisticated ecological analysis that allows for detailed management outcomes that are unique to place and system (Cleverly et al., \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Zurell et al., \u003cspan citationid=\"CR98\" class=\"CitationRef\"\u003e2020\u003c/span\u003e, Perry et al., \u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe emerging practice of holistic ecological monitoring is tied to a growing awareness of the importance of better knowledge of environmental conditions, as well as social and economic prosperity, to advance sustainable development (Jaegar et al., 2008; Ferrario et al., 2022). Holistic environmental monitoring aims to develop a comprehensive representation of a landscape integrated in its wider ecological context (Ferrario et al., 2022). The concept of adaptive co-management acknowledges the importance of social networks and norms between stakeholders for improved collaboration to manage systems to respond to disturbances and adapt to change (Armitage, \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Cundill and Fabricius, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Bardsley et al., \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Adaptive co-management emphasises learning-by-doing through monitoring and action (Walters and Holling, \u003cspan citationid=\"CR92\" class=\"CitationRef\"\u003e1990\u003c/span\u003e; Daniels and Walker, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2001\u003c/span\u003e), with a focus on collaborative and inclusive decision-making (Borrini-Feyerabend, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Carlsson and Berkes, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2005\u003c/span\u003e). Reflexivity and social learning as developed in the context of environmental management are conceptually related to adaptive co-management and particularly important for social aspects of a transition in an NRM approach. Reflexivity refers to an individual or group's ability to examine themselves in relation to their actions and interactions with others (Pienkowski et al. \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Social learning has been defined as a process of learning through collective, iterative reflection (Keen et al., 2005; Fernandez-Gimenez et al., \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2008\u003c/span\u003e) or a learning outcome, such as a change in conceptions or attitudes, which becomes social learning when it is diffused through a larger network via social interaction (Reed et al., 2010). Gauging stakeholders\u0026rsquo; awareness and practice of, or enthusiasm for measures resembling holistic monitoring and adaptive co-management will assist in determining how systematic monitoring in Australia may be further developed to ensure adaptive, evidence-based policy. In other words, without knowledge of the social processes that will enable change in monitoring, Australians and international stakeholders could struggle to understand change within the nation\u0026rsquo;s ecological systems or develop the adaptive capacity to manage future ecosystems.\u003c/p\u003e \u003cp\u003eIssues in ecological monitoring within socio-ecological systems can be harder to manage than those within natural systems, as the former rely upon strategic behaviours of stakeholders and there are often limitations to controlled experimentation in anthropogenic systems (Sabatier, \u003cspan citationid=\"CR80\" class=\"CitationRef\"\u003e1995\u003c/span\u003e). Therefore, scientists are increasingly being called to embrace multidisciplinary approaches, including social science research, to better understand and resolve socio-cultural challenges to effective environmental management and monitoring (Ferrario et al., 2022).\u003c/p\u003e \u003cp\u003eSignificant portions of the relevant literature on social processes influencing monitoring specifically discuss \u0026lsquo;community monitoring\u0026rsquo; or monitoring via \u0026lsquo;citizen science\u0026rsquo; programs (e.g. Wiseman and Bardsley, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Danielsen et al., \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Bonney et al., \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Alblas and van Zeben, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Methods of monitoring with community participation are often diverse in how they employ local, traditional and scientific knowledge, which can undermine the integrity of the data generated (Danielsen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). For example, community-based monitoring in Australia\u0026rsquo;s rangeland environments is constrained by sparse human populations across large areas and by resource-limited regional bodies that are distanced from centres of economic and political power (Reynolds et al., \u003cspan citationid=\"CR75\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; White et al., \u003cspan citationid=\"CR93\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). These disadvantages are concentrated within remote Indigenous communities due to political, socio-economic, and cultural marginalisation within Australian society (Davies et al., \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2008\u003c/span\u003e; AW NRM Board, 2013). There is impetus for Australia to better integrate Indigenous community-based monitoring into regional environmental management (Wiseman and Bardsley, \u003cspan citationid=\"CR96\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Thompson et al., \u003cspan citationid=\"CR88\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Systems such as EMSA could help to improve the effectiveness of holistic community-based monitoring by standardising approaches to data collection, management and sharing, thereby improving processes and outcomes even for individuals or groups in remote locations. Beyond such an aim, too little is understood of professional actors\u0026rsquo; perceptions of decision-making, enactment and analysis regarding ecological monitoring. By examining how those professionals perceive the transition to a standardised national approach to ecological monitoring, we can explore the socio-cultural framing of monitoring to generate knowledge on why and how it could best be implemented.\u003c/p\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e3.1. Achieving social change for successful ecological monitoring standardisation\u003c/h2\u003e \u003cp\u003eSocial tensions in association with monitoring programs can undermine environmental management success. Such social conflict may be particularly difficult to resolve because scientists tend to focus on data and hypotheses, and can underestimate other values key to the social processes of environmental monitoring and management (Sabatier and Jenkins-Smith, \u003cspan citationid=\"CR79\" class=\"CitationRef\"\u003e1993\u003c/span\u003e; Doremus, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2007\u003c/span\u003e). In response, there are a range of methods emerging for overcoming social conflict during technical transitions and facilitating successful monitoring outcomes.\u003c/p\u003e \u003cp\u003eThe importance of education for overcoming socio-cultural barriers to ecological monitoring standardisation is now well established. If stakeholders hold entrenched negative perceptions of an approach for reasons that lack strong evidence, education can fill gaps in understanding (Sharma and Monterio, 2016). NRM service providers have identified that they are open to adopting a standard method if they can see the value of the approach (Cox, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Indeed, previous research suggests that the better participants understand the objectives and value of a program, the more closely they will follow procedures accurately (Gitzen et al., \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Biber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). For example, flexibility is allowed within EMSA to record information beyond that data which is strictly required by the protocols, which will be important both for maintaining participant interest and guiding evolution of the monitoring approach over time. It has been recommended that service providers be supported through education and stewardship programs that demonstrate the intrinsic value of a standardised methodology (Cox, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). In fact, part of the goal of this research is to inform training to accompany EMSA implementation.\u003c/p\u003e \u003cp\u003eAnother method of overcoming socio-cultural challenges to effective monitoring is through the development of mutual understanding to enable collaboration among stakeholders (Allen et al., \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Biber, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Johannsson et al., 2022). Many successful long-term monitoring studies are built on partnerships between people with differing but complementary skills, including those concerned with the human dimensions of ecological monitoring, such as policy-makers (Danielsen et al., \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2009\u003c/span\u003e; Lindenmayer et al., \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Ferrario et al., 2022). Such a transdisciplinary approach increases the relevance and impact of long-term ecological monitoring (Lynch et al., \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). While improved communication between stakeholder groups may be sufficient for addressing low-level disagreements (Sanchirico et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), collaborative monitoring, where conscious information seeking is followed by shared critical analysis, has been found to promote learning and consensus building to inform NRM decisions (Cundill and Fabricius, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2009\u003c/span\u003e). Increasingly, such collaboration is expanding to include professionals beyond science, whose work involves the socio-cultural aspects of monitoring, such as social scientists, economists, and artists (e.g. Robin et al., \u003cspan citationid=\"CR76\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Sanchirico et al., \u003cspan citationid=\"CR81\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Opportunities for scientists, managers, industrial and public stakeholders to meet and exchange experiences and expectations can facilitate multidisciplinary monitoring projects. By investigating stakeholders\u0026rsquo; experiences of collaboration with DCCEEW during the development of EMSA, this research also initiates a process of informing future opportunities for such collaboration.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Methods","content":"\u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e4.1. TERN focus groups\u003c/h2\u003e \u003cp\u003eA qualitative approach was undertaken to review perceptions of the introduction of the EMSA protocols amongst NRM practitioners and other key stakeholders (Grypma et al., \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Two preliminary focus groups were conducted with TERN staff involved in developing EMSA, to discern any socio-cultural challenges they anticipate or have encountered while engaging other stakeholders during the protocol development process. The first focus group involved five EMSA staff who were involved in a project support officer capacity, and the second involved two staff who were primarily involved in project management and communications. Each focus group ran for approximately one hour and twenty minutes.\u003c/p\u003e \u003cp\u003eFocus groups are regularly used to evaluate program and policy implementation (Ryan et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Asking stakeholders, through a focus group, to identify potential barriers to program implementation before a program has started is an effective method of rapidly informing program implementation at minimal cost (Gilmartin et al., \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). Focus groups are also a valuable starting point to investigate the socio-technical context in which TERN operates. The discussions provided initial context and depth of understanding regarding stakeholders\u0026rsquo; thoughts and experiences pertaining to EMSA (Ryan et al., \u003cspan citationid=\"CR78\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). Therefore, the focus groups assisted in planning the stakeholder interviews by providing key points of consideration for interviews. Participants were emailed the list of discussion questions a week prior to their session and were invited to individually note their responses to the questions in their own time. The three pre-prepared questions most relevant to socio-cultural challenges to EMSA implementation then guided the group discussions. Notes taken during the focus group focussed on the participants\u0026rsquo; verbal responses and prompted follow-up questions, while audio recorded and transcribed data ensured quotes were accurately captured.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003e4.2. Semi-structured interviews\u003c/h2\u003e \u003cp\u003eThe majority of primary data for this study was collected through twenty semi-structured interviews. Interviews were conducted with a diverse range of stakeholders who have, or will soon be, engaging with EMSA in their work. This included those involved in developing and managing EMSA, those who will be involved in collecting data through protocol implementation, and those involved in using the resultant data via the BDR. Specifically, participants included ecologists from both government agencies and academia, NRM staff involved in project design and reporting, and DCCEEW Nature Positive Integration division staff [See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e]. Together with the focus group data, the interviews highlight the wide range of perceptions that exist in relation to standardised ecological monitoring in Australia. This study is unique in its examination of the perceptions of ecological monitoring standards and system developers, data collectors and end-users in conjunction (Cf. Alblas and van Zeben, \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Chase and Levine, 2018). This feature allows for comparison of the observations and opinions of these cohorts, enabling the development of a holistic picture of the socio-cultural processes of standardising ecological monitoring in Australia.\u003c/p\u003e \u003cp\u003eInterviews ranged in length from forty-five to ninety minutes and were conducted either Face-to-Face or via Zoom. In the pursuit of anonymity, interviewees are referred to by general descriptors of their roles [See Table\u0026nbsp;4.1]. It was important to differentiate the participants in this manner in order to compare and distinguish responses by background. \u0026lsquo;NRM coordinator\u0026rsquo; refers to a person who works as a conduit or facilitator of knowledge sharing between EMSA stakeholder groups such as NRM regions, state and commonwealth government agencies. \u0026lsquo;End-user\u0026rsquo; refers to a representative of an organisation that will make use of the ecological monitoring data produced by EMSA. This method of participant anonymity was designed in accordance with the National Statement on Ethical Conduct in Human Research and approved by the University of Adelaide Human Research Ethics Committee (approval number H-2023-126).\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section3\"\u003e \u003ch2\u003e4.2.1. Interview participant selection\u003c/h2\u003e \u003cp\u003eThe small sample size of the focus groups and interviews does not intend to be socially representative or comprehensive. Rather, the sample was stratified to obtain responses from a range of key stakeholders to generate textured, in-depth findings through discussions with a variety of stakeholders. First, the researchers compiled a list of potential participants in association with the NRM Regions Australia Knowledge Broker to ensure a variety of stakeholders of different backgrounds and at different levels of their organisation were interviewed. The method is consistent with statistically non-representative stratified sampling, as variables were defined based on a hypothesis that those of different backgrounds will encounter or generate different socio-cultural challenges to EMSA implementation (Trost, \u003cspan citationid=\"CR89\" class=\"CitationRef\"\u003e1986\u003c/span\u003e). Variables included stakeholder organisation (e.g. government or NRM service provider), region of Australia working within, and nature of engagement with EMSA (e.g. as a developer, data collector or end-user) [See Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eSemi-structured interviews: EMSA stakeholders\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"2\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eType of stakeholder\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNumber of interviews conducted\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRM region professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e10 consisting of:\u003c/p\u003e \u003cp\u003e● 2 with Tasmanian regions,\u003c/p\u003e \u003cp\u003e● 3 with South Australian regions,\u003c/p\u003e \u003cp\u003e● 2 with New South Wales regions,\u003c/p\u003e \u003cp\u003e● 1 with a Western Australian region,\u003c/p\u003e \u003cp\u003e● 1 with a Victorian region, and\u003c/p\u003e \u003cp\u003e● 1 with a Queensland region.\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDCCEEW EMSA professional\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNRM coordinator\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEnd-user\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAcademic researcher\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e4.3. Thematic analysis\u003c/h2\u003e \u003cp\u003eTo ascertain and interpret key perceptions and socio-cultural challenges to EMSA implementation based on the focus groups and interviews conducted, the data was analysed using techniques of thematic analysis, as set out by Braun and Clarke (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). Following transcription, the focus group data, including individual participant written responses, and each interview was read through and initial analytic insights noted. This familiarised the researchers with the entire dataset. Subsequently, the process of generating and elaborating concepts was commenced using the interpretative, inductive techniques of coding. Coding was both semantic (capturing the explicit or surface meaning) and latent (capturing more conceptual or implicit meaning) (Braun and Clarke, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2021\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eConsistency and accuracy of coding was achieved and the intrusion of bias limited, through application of the techniques of constant comparison and questioning (Corbin and Strauss, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2015\u003c/span\u003e; Glaser and Strauss, \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e1967\u003c/span\u003e). Constant comparison involves examining data both within and between documents (i.e. transcripts) to group together data that are conceptually similar. Questioning involves asking various questions of the data in order to draw meaning from them. Typical questions included, \u0026lsquo;What are the issues, problems, and concerns here?\u0026rsquo;, \u0026lsquo;Who are the actors involved?\u0026rsquo; and \u0026lsquo;How do they define the situation?\u0026rsquo;. Following an informal coding process, concepts were integrated where appropriate and grouped into broader themes and key messages. We summarise the key findings from the qualitative data using tables, and elaborate on key themes with evidence warranted from the qualitative data following the approach taken by Bardsley et al. (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2023\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Results","content":"\u003cp\u003eThis section presents the key findings from the focus groups and interviews. The thematic analysis revealed a range of perceived potential advantages of EMSA [Table 2], but in the analysis below we emphasise the perceived socio-cultural challenges relating to EMSA and its implementation [Table 3].\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"990\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.606060606060606%\"\u003e\n \u003cp\u003eAdvantage of EMSA mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.39393939393939%\" colspan=\"22\"\u003e\n \u003cp\u003eRespondent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.62689585439838%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.34479271991911%\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eNRM region professionals\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.672396359959555%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cem\u003eDCCEEW EMSA professionals\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.381193124368049%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eNRM knowledge brokers\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.381193124368049%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eEnd-users\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.077856420626896%\"\u003e\n \u003cp\u003e\u003cem\u003eAcademic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.460060667340748%\"\u003e\n \u003cp\u003e\u003cem\u003eTERN focus groups\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.055611729019211%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eEnable/validate national ecological research\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e17/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eHigh quality national level information\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e17/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eAccountability for public funding\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e14/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eReliable collection and storage of data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e13/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eGuide reporting (e.g. SOE, international)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e12/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eEnable reproducible science-based monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e11/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eEnable longevity of ecological monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e9/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eEasily accessible data\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e8/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eFlexible \u0026nbsp;systems that adapt to needs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e8/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eCreate efficiencies in data collection/ management/ use\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e8/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eNormalisation of national-scale monitoring\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e6/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.585267406659938%\"\u003e\n \u003cp\u003eEnable investment in ecological outcomes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.1281533804238144%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.7336024217961654%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.063572149344097%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.449041372351161%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.045408678102926%\"\u003e\n \u003cp\u003e6/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cp\u003e\u0026nbsp; Table 2. Key advantages of EMSA perceived by stakeholders\u003c/p\u003e\u003cbr\u003eTable 3. Key socio-cultural challenges of EMSA perceived by stakeholders\u0026nbsp;\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"994\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eSociocultural challenge\u0026nbsp;mentioned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"79.5774647887324%\" colspan=\"22\"\u003e\n \u003cp\u003eRespondent\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"31.187122736418512%\" colspan=\"10\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003cp\u003e\u003cem\u003eNRM region professionals\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"15.593561368209256%\" colspan=\"5\"\u003e\n \u003cp\u003e\u003cem\u003eDCCEEW EMSA professionals\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.645875251509055%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eNRM knowledge brokers\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.645875251509055%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eEnd-users\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\"\u003e\n \u003cp\u003e\u003cem\u003eAcademic\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\"\u003e\n \u003cp\u003e\u003cem\u003eTERN focus groups\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003eTotal\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\"\u003e\n \u003cp\u003e15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\"\u003e\n \u003cp\u003e18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\"\u003e\n \u003cp\u003e20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\"\u003e\n \u003cp\u003e21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eInsufficient capacity to implement protocols\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e21/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eData utility and access for regional projects\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e18/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eAdaptability of EMSA protocols/tools/system\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e18/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eCommunications regarding EMSA roll-out\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e15/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eAttachment to current practices\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e15/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eDemonstration of clear EMSA purpose/value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e13/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eGiving and responding to feedback\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e12/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eWeaken local relationships and knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e11/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eNeed to see short-term advantages\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e11/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eCommonwealth/State government coordination\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e10/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eInitial EMSA development consultation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e10/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"20.422535211267604%\"\u003e\n \u003cp\u003eAutonomy of NRM regions\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.118712273641851%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003ex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"3.8229376257545273%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"7.042253521126761%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.4325955734406435%\" valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"5.030181086519114%\"\u003e\n \u003cp\u003e7/21\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003e5.1. Insufficient capacity to carry out EMSA protocols\u003c/h2\u003e\n \u003cp\u003eRespondents noted that natural resource management, and ecological monitoring in particular, is not well resourced. All respondents raised the issue of adequate financial and labour resources being required to facilitate the transition to systematic monitoring, especially in regional and remote areas. Some highlighted that the potential for a lack of financial support was their primary concern regarding EMSA protocol implementation.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eOur biggest concern is that we can\u0026apos;t implement [the EMSA protocols] because we\u0026apos;re not resourced to implement them. They will add considerably to the cost of our operations, and if that [cost] has to come out of projects, we might say \u0026ldquo;We won\u0026apos;t achieve these outcomes on the ground, and [instead] we\u0026apos;ll spend [funds] on monitoring the limited outcomes that we\u0026apos;ve achieved.\u0026rdquo; (NRM region professional 4)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003ePart of that concern originates from the recent shift in the way NRM activities are funded by the Commonwealth Government from a grant-based funding model to a procurement model, which largely assigns NRM regions with the role of a service provider (Rolfe et al., \u003cspan\u003e2017\u003c/span\u003e). Respondents noted that this method of funding gives the Commonwealth more power to demand particular outcomes, which regions may struggle to apply. NRM funding cycles run over short time periods and do not sufficiently cover many key management operations over the longer term. Stakeholders were concerned that EMSA implementation would generate additional bureaucratic burdens limiting time to develop understanding of local issues or implementing appropriate management interventions.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe realistic impact that you can have in five years with the dollars provided is sometimes quite limited. Sometimes partnerships and engagement are the main outcome\u0026hellip; For example, you\u0026rsquo;ve managed to get a memorandum of understanding with a traditional owner group\u0026hellip; [in that case] you\u0026apos;re not paying for an environmental outcome, and you need to be clear, \u0026ldquo;In the next five years, we\u0026apos;re just scratching the surface of trying to fix this problem.\u0026rdquo; The TERN protocols are [irrelevant] in that situation. (NRM region professional 3)\u003c/p\u003e\n \u003cp\u003eHow difficult is it to establish relationships with businesses, land councils and enterprises in remote regions, from Canberra, over a 4 to 5 year period? And then pull funding, or know funding is going to end, or maybe keep going into the next programme\u0026hellip; (DCCEEW EMSA professional 15)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003ch2\u003e5.1.1. Data utility and access for regional projects\u003c/h2\u003e\n \u003cp\u003eData is used all the time by local and regional environmental management groups to review outcomes of environmental management interventions and make decisions for future actions. A widespread concern emphasised by NRM region professionals was that data gathered utilising the EMSA protocols and associated tools would not reveal whether their local projects, including Commonwealth funded activities, are producing desired outcomes.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eWhat the Commonwealth tends to revert to is measuring biodiversity the same way everywhere, at a national level. You get this complete incongruence with what they\u0026apos;re investing in, which is very local, and what they\u0026apos;re measuring\u0026hellip; that means they run into problems. I think there\u0026apos;s also a social element: you\u0026apos;re engaging regional boards, staff and communities in a process which is very local to them, and then you\u0026apos;re asking them to engage in this evaluation process, which has nothing to do with them. Essentially, you\u0026apos;re asking them to go out and measure things which, from their perspective, have no bearing on whether they\u0026apos;re being effective or not. (NRM Coordinator 17)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAnother widespread concern was that EMSA data would not be readily available in a form that they could use to easily make decisions or verify actions. While the protocols are organised to provide baseline data that could answer a range of ecological questions, such scientific analysis could be difficult to implement at regional scales. In fact, several respondents argued that the best outcomes came when high quality monitoring could be undertaken locally with limited external interference.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eWe haven\u0026apos;t been given any indication how we get our data back. We know we have to enter data into the app, and it goes into the Biodiversity Data Repository, but there is no indication of how we get it back, and no indication of what we do with it then, because if you have one plot with thousands of individual data points in it; that\u0026apos;s beyond the capacity of a lot of NRMs to analyse. (NRM region professional 2)\u003c/p\u003e\n \u003c/div\u003e\n \u003ch2\u003e5.1.2. Adaptability of EMSA protocols, tools and system\u003c/h2\u003e\n \u003cp\u003eFinally, the collection, storage and utilisation of high-quality ecological data was the other major theme raised by more than 85% of participants. They emphasised that the EMSA protocols, tools and systems need to be made adaptable to suit unique ecological circumstances, with the capacity to evolve as implementation commences and technical or logistical issues are identified.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eI think [the protocols] are pretty flexible, but plot size will be a primary limiting factor, and [ensuring the protocols can be used with] different plot sizes is something that we\u0026apos;re going to explore. There will be heaps of situations where you need to adjust plot size, and at the moment there isn\u0026apos;t flexibility to do that, but a lot of the protocols are fairly broad. They have been designed to be applicable to different systems. There may be a period of figuring out how things need to be changed or adapted to capture everything. (TERN focus groups)\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n \u003cdiv id=\"Sec14\"\u003e\n \u003ch2\u003e5.2. Communication, collaboration and education\u003c/h2\u003e\n \u003cp\u003eIn a third set of questions, we asked respondents to elaborate on approaches they were suggesting to support EMSA implementation. Most responses linked to the most important issues highlighted above, with ideas for either better exploitation of opportunities from systematic ecological monitoring, or avoidance of potential negative impacts or constraints.\u003c/p\u003e\n \u003cdiv id=\"Sec15\"\u003e\n \u003ch2\u003e5.2.1. Opportunities to give feedback and receive responses\u003c/h2\u003e\n \u003cp\u003eAbout half of respondents acknowledged giving and responding to feedback as an important social process to engage in during EMSA implementation. While opportunities for communication had been made available to regional stakeholders, they felt there was insufficient acknowledgement or incorporation of that feedback into co-design of the protocols or monitoring approach. This may have negatively influenced perceptions of EMSA early on and made some regional NRM professionals sceptical of the worth of further engagement with the process.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eIt didn\u0026apos;t feel like genuine consultation. There was no in-depth consultation, particularly on what NRM needs are, and how it would actually work\u0026hellip; There was a spreadsheet sent out for feedback. I asked nine questions, and nothing happened\u0026hellip; I chased it up: \u0026ldquo;I haven\u0026apos;t gotten any answers.\u0026rdquo; I\u0026apos;ve since received answers to four of my questions\u0026hellip; This [interview] is the first proper opportunity I\u0026apos;ve had to provide any feedback to the department. (NRM region professional 2)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eThere is a communication challenge to explain complex scientific decisions that aim to meet universal goals on a general scale that will respond to all regional concerns. For example, some feedback ideas on draft protocols could not be appropriately integrated into the approach, but this might not have been effectively communicated to regional groups.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eThroughout the whole project, we\u0026apos;ve repeatedly told [NRM service providers] what we\u0026apos;re doing. We\u0026apos;ve asked them for feedback. We\u0026apos;ve gotten very little feedback, and the feedback we have gotten hasn\u0026apos;t been of any use anyway. That\u0026apos;s probably why we haven\u0026apos;t engaged as much as we probably should have. (TERN focus groups)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eTherefore, A key narrative was that a major transition in a scientific approach would benefit from regular communication and greater direct participation from key stakeholders to ensure changes are understood and to facilitate ownership of new technical processes. In fact, several stakeholders argued that NRM service providers should have been far more directly involved in the initial phase of crafting a solution to the problem of inadequate ecological monitoring.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eI don\u0026apos;t feel the NRM sector was at all involved in the discussion of how we can make things better. Before going to TERN and saying \u0026ldquo;Solve this problem for us\u0026rdquo;, have this conversation with the regions. They\u0026apos;ve got us out there in the regions that they\u0026apos;re contracting projects with, we know better than anyone about the implementation side, and I feel like we weren\u0026apos;t consulted at all. (NRM region professional 6)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAuthentic engagement with NRM stakeholders will be important as EMSA implementation continues. One idea suggested by numerous respondents was the importance of multimodal training in EMSA to assist in building relationships and confidence in the new system.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eWhen the [state-based] vegetation benchmarks project was rolled out\u0026hellip;we went through a 2.5-year training process - the focus was on training left, right and centre to target as many people as possible - and we\u0026apos;re still trying to encourage the uptake of that methodology. (NRM region professional 4)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eSome volunteer groups, such as citizen scientists, may be more reluctant to apply the protocols and use the app and related systems. One suggestion was for further face-to-face engagement with NRM sub-regional partners, who in turn could become change-leaders within their region. Some regions or groups with less capacity or unique monitoring needs may need targeted direct training and on-going assistance to effectively integrate the protocols into their monitoring systems.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eI think having champions associated with [EMSA] is really important. There are a lot of events that happen in the bush, where you can just book an hour to be face-to-face with people. There\u0026apos;s nothing better. Once you get key people on side, then the ideas will spread and be taken up. (Academic)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003eAlthough it was beyond the scope of the initial phase of EMSA development, the co-design of regional projects was also seen as a highly valuable tool for successful implementation in the future. The negotiation of projects in association with monitoring, and the choice of application of particular protocols suited to local needs would be a vital step in the acceptance of the new monitoring approach.\u003c/p\u003e\n \u003cdiv\u003e\n \u003cp\u003eI\u0026rsquo;d like to see more intensive engagement with us as delivery partners for this type of work. We [could] assess the protocols and their applicability [together with DCCEEW]. I hope there\u0026rsquo;s a fair bit of opportunity to opt-out where we can justify why we\u0026apos;re not following those protocols. Because some of the work we do is simply community engagement. It\u0026apos;s not about collecting rigorous monitoring data. (NRM region professional 5)\u003c/p\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n \u003c/div\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"6. Discussion","content":"\u003cp\u003eThis study demonstrates how an array of complex social, institutional, and ecological issues, operating at various scales, emerge from a change in scientific approach within a community. Acknowledgement of the diversity of experiences of monitoring standardisation within the NRM community is a first step in resolving that complexity. Complex systems require a multivariate, integrated approach to environmental management (Bellamy et al., \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2001\u003c/span\u003e; Cundill and Fabricius, 2008), and governance approaches like adaptive co-management have come about as a means of dealing with such complexity and uncertainty (Ollson et al., 2004). These approaches rely on collaboration among a diverse set of actors, and on social coordination whereby actions are coordinated by stakeholders in a self-organising and self-enforcing manner. Stakeholders requested more autonomy and flexibility throughout our research, so their involvement in how the protocols evolve would enable NRM practitioners to coordinate associated actions and self-organise to facilitate appropriate regional methods for monitoring standardisation.\u003c/p\u003e \u003cp\u003eOur findings indicate that reflexivity is a vital concept to address the complexity involved in standardisation of ecological monitoring. New approaches to environmental management will increasingly have to account for the complexity of socio-ecological systems in order to overcome the unprecedented challenges that will arise in the wake of future global change. While both informal and institutionalised reflexivity require allocation of limited time and resources, when intentionally undertaken, reflexive processes can be integrated into adaptive management at multiple points, helping environmental management stakeholders better reach their goals (Mol, \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e1996\u003c/span\u003e; Pearson and Bardsley, \u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Pienkowski et al., \u003cspan citationid=\"CR72\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Reflexivity plays a transformative role, supporting practitioners to learn to regularly reevaluate their goals and methods to meet changing needs. Although the term was not mentioned, the participants in this study expressed a deep understanding of and desire for reflexive approaches to monitoring standardisation. EMSA itself is the outcome of a comprehensive re-evaluation of Australian ecological monitoring and reporting, and the need for standardisation was endorsed as a response to the shortfalls of current monitoring practice. The major concerns of protocol adaptability, consequent data utility, lack of consultation and adequate opportunities to give feedback conveyed by NRM stakeholders are essentially concerns of a lack of reflexivity to date within EMSA implementation.\u003c/p\u003e \u003cp\u003eThe lack of resourcing of Australian NRM in general, and concerns with insufficient extra support for this \u0026lsquo;upgrade\u0026rsquo; of ecological monitoring in Australia, emerged as the key narrative. As learning and re-evaluation takes time, reflexive approaches are more expensive than simple knowledge transfer systems. Importantly, our results show that capacity limitations are not only about funding, but also relate to an NRM organisation\u0026rsquo;s ability to take the time to engage in, and benefit from, collaboration and learning activities. Aside from providing more funding, making social learning an explicit objective of the change process is necessary to build social capacities (Fern\u0026aacute;ndez-Gim\u0026eacute;nez et al., \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Dimmock et al., \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; LoSchiavo et al., \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Therefore, resourcing for EMSA implementation needs to not only update tools and technical activities, but also facilitate learning processes to generate the social licence for the new monitoring system. Our results support this conclusion, with respondents calling for multimodal training, the development of local champions to spearhead implementation, and co-design of projects utilising the protocols.\u003c/p\u003e \u003cp\u003eImproved communication between researchers and applied sectors has been proposed as a practical step towards enhancing collaboration for adaptive environmental management (Brownson and Fowler, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2020\u003c/span\u003e; Allan and Watts, 2017; Hagell and Ribic, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2014\u003c/span\u003e). When researchers work closely with science end-users, constructive change is enabled because collaboration can immediately and directly address social obstacles. Trust building, dialogue and active involvement have been identified as among the most recognised qualities of collaboration (Fiest et al., 2020). Respondents\u0026rsquo; concerns about a perceived lack of genuine consultation and acknowledgement of feedback, reveal the importance of clear communication at all stages of an environmental management project that aims to standardise and streamline practices. As M\u0026aring;nsson et al. (2023) also argue, by developing understanding of the socio-cultural challenges to the implementation of a new environmental management approach, our research demonstrates the advantages of such transdisciplinary learning to inform the standardisation of ecological monitoring.\u003c/p\u003e"},{"header":"7. Conclusion","content":"\u003cp\u003eEnvironmental management stakeholders are not opposing the standardisation of ecological monitoring. However, as a unifying approach to monitoring data is applied, differentiated methods and approaches to suit local contextual situations and desired outcomes are crucial to successful implementation. Reflexivity is already starting to be built into EMSA implementation through opportunities for project co-design and protocol opt-out, but there are also key social processes beyond these mechanisms related to the transition that will need to be developed in the future.\u003c/p\u003e \u003cp\u003eThere are both important academic and practical values in undertaking research to analyse how transitions in ecological monitoring will be accepted by scientific and NRM communities. Social knowledge on how best to implement technological and procedural change will be vital to inform a new era in environmental management: an era that will increasingly incorporate environmental change; green investment; regeneration of multifunctional landscapes; increasing natural hazard risk; and a broad range of new relationships between people and their ecology. In this case, the normalisation of high-quality national level ecological monitoring to achieve an improvement in the understanding of the national environment, and increased accountability of funding for public investment were the most widespread perceived advantages. The most commonly perceived socio-cultural challenges centred around the adaptability of EMSA methodologies for NRM service providers, and the need for adequate resourcing and prioritisation of relationships with stakeholders. To respond to such socio-ecological complexity, strong participatory approaches will be needed to develop effective technical solutions. In fact, it is possible to argue that mutual social learning between scientists and practitioners that can enable ownership of the new approach and lead to co-design of policy and practice must be normalised to guide effective transitions in environmental management.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cu\u003eAcknowledgements\u0026nbsp;\u003c/u\u003e\u003c/p\u003e\n\u003cp\u003eThis research is part of a body of work funded by the Australian Government Department of Climate Change, Energy, the Environment and Water (DCCEEW). TERN is funded by the National Collaborative Research Infrastructure Strategy.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThis research was approved by the University of Adelaide Human Research Ethics Committee (approval number H-2023-126).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAlblas, E \u0026amp; van Zeben, J 2023, \u0026lsquo;Public participation for a greener Europe: The potential of farmers in biodiversity monitoring\u0026rsquo;, \u003cem\u003eLand Use Policy\u003c/em\u003e, vol. 127, p. 106577. https://doi.org/10.1016/j.landusepol.2023.106577 \u003c/li\u003e\n\u003cli\u003eAllan, C \u0026amp; Watts, RJ 2018, \u0026lsquo;Revealing Adaptive Management of Environmental Flows\u0026rsquo;, \u003cem\u003eEnvironmental Management (New York)\u003c/em\u003e, vol. 61, no. 3, pp. 520\u0026ndash;533. https://doi.org/10.1007/s00267-017-0931-3 \u003c/li\u003e\n\u003cli\u003eAllen, CR, Fontaine, JJ, Pope, KL \u0026amp; Garmestani, AS 2011, \u0026lsquo;Adaptive management for a turbulent future\u0026rsquo;, \u003cem\u003eJournal of Environmental Management\u003c/em\u003e, vol. 92, no. 5, pp. 1339\u0026ndash;1345. https://doi.org/10.1016/j.jenvman.2010.11.019 \u003c/li\u003e\n\u003cli\u003eArmitage, D 2005, \u0026lsquo;Adaptive capacity and community-based natural resource management\u0026rsquo;, \u003cem\u003eEnvironmental Management (New York)\u003c/em\u003e, vol. 35, no. 6, pp. 703\u0026ndash;715. https://doi.org/10.1007/s00267-004-0076-z \u003c/li\u003e\n\u003cli\u003eAW NRM Board (Alinytjara Wilurara Natural Resources Management Board) 2013, \u003cem\u003eAmendments to the Regional Natural Resources Management Plan of the Alinytjara Wilurara\u003c/em\u003e, Natural Resources Management Board, Government of South Australia, Adelaide.\u003c/li\u003e\n\u003cli\u003eBardsley, DK \u0026amp; 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Ecological monitoring provides vital information for decision-makers and natural resource management practitioners to make informed environmental management decisions. For a long time, ecological monitoring across Australia has utilised a wide variety of different methodologies resulting in data that is difficult to analyse across place or time. Much of the ecological data that is currently generated in incomparable with other data or it has been collected using inappropriate methods for the intended aims. In response to these limitations, a new systematic approach to ecological monitoring has been developed in collaboration between the Terrestrial Ecosystem Research Network and the Australian Department of Climate Change, Energy, the Environment and Water - the Ecological Monitoring System Australia. We found that environmental management stakeholders are not opposing the standardisation of ecological monitoring. However, key concerns emerged regarding the capacity needed to implement the standard protocols, the utility of the resultant data for regional projects, and the adaptability of the EMSA. Stakeholders emphasised the need for autonomy and flexibility, so their participation in protocol development can facilitate regional adoption of the standards. Respondents\u0026rsquo; concerns about a perceived lack of genuine consultation and acknowledgement of feedback revealed the importance of clear communication at all stages of an environmental management project aiming to standardise practices. New approaches to environmental management will increasingly have to account for the complexity of socio-ecological systems in order to overcome the unprecedented challenges that will arise in the wake of future global change.\u003c/p\u003e","manuscriptTitle":"The critical social processes for standardising the ecological monitoring of Australian landscapes","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-03 16:29:02","doi":"10.21203/rs.3.rs-4337606/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-06-14T00:39:58+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-13T20:42:35+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-12T21:44:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-06-08T02:33:00+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"167702143942619731244900507108839372162","date":"2024-05-17T15:39:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209909981571764102890031207748080323070","date":"2024-05-17T14:43:54+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"331838478863086077304566900496820642318","date":"2024-05-17T03:21:40+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-05-17T02:31:27+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-02T01:29:11+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-04-29T06:26:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Environmental Management","date":"2024-04-28T11:02:00+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"environmental-management","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"emvm","sideBox":"Learn more about [Environmental Management](http://link.springer.com/journal/267)","snPcode":"267","submissionUrl":"https://submission.nature.com/new-submission/267/3","title":"Environmental Management","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"7506a409-5f54-43b4-9eb2-1c533c3c663e","owner":[],"postedDate":"May 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-09-30T16:09:13+00:00","versionOfRecord":{"articleIdentity":"rs-4337606","link":"https://doi.org/10.1007/s00267-024-02049-2","journal":{"identity":"environmental-management","isVorOnly":false,"title":"Environmental Management"},"publishedOn":"2024-09-26 15:56:52","publishedOnDateReadable":"September 26th, 2024"},"versionCreatedAt":"2024-05-03 16:29:02","video":"","vorDoi":"10.1007/s00267-024-02049-2","vorDoiUrl":"https://doi.org/10.1007/s00267-024-02049-2","workflowStages":[]},"version":"v1","identity":"rs-4337606","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4337606","identity":"rs-4337606","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}