The contribution of indigenous traditional knowledge to environmental management, including protection of biological heritage from biosecurity risks and threats, is important globally because it offers long-term knowledge on the state of the biological, physical, and spiritual environments (Berkes and Berkes, 2009; Gagnon and Berteaux, 2009; Berkes, 2017; Wehi and Lord, 2017). This level of knowledge and understanding of the environment, acquired and passed on across generations, gives rise to a distinctive perspective on underlying ecosystem structures which can contribute towards more robust biosecurity outcomes (Kuru et al., 2021). Furthermore, adoption of indigenous values can result in meaningful involvement and a greater chance of long-term success as indigenous groups can see benefits, in the form of economic returns and upholding of cultural values, from involvement in incursion responses or long-term management of forest pests and pathogens (Wehi and Lord, 2017).

In Aotearoa New Zealand, many hapū/iwi generate and continually update information on biodiversity and ecosystems at fine spatial resolutions through engagement at place with their environment, share this knowledge broadly through sophisticated social and extended familial networks, and pass it down through generations. The Māori worldview sees people as having deeply interconnected and interdependent relationships with their natural environment, elevates the wellbeing of future generations above that of current generations, and places the status of nature above that of humans in any environmental decision making. Despite its importance and the protection of rights, interests and property of Māori guaranteed within Te Tiriti o Waitangi, mātauranga Māori is seldomly regarded or adopted as a valid and relevant knowledge system that can inform regional and national biosecurity (Lambert et al., 2018; Black et al., 2019). In this context, the challenge has been to recognise that both te ao Māori and empirical scientific knowledge systems have an equitable responsibility and part to play in the protection of people and places (Lambert et al., 2018).

Plant pathogens are of great concern globally because of the severe detrimental impacts they can have on environmentally, economically, and culturally significant flora and fauna (Koblentz, 2010; Chakraborty and Newton, 2011; Singh et al., 2023). In Aotearoa New Zealand there are two serious diseases of native flora. Kauri dieback – caused by the microscopic soilborne pathogen Phytophthora agathidicida – is devastating the remnants of iconic native kauri (Agathis australis; Waipara et al., 2013). Kauri are considered a taonga by Māori and a species of special significance to many New Zealanders. Myrtle rust – caused by the airborne rust fungus Austropuccinia psidii – threatens several of Aotearoa New Zealand’s native myrtle species, such as iconic pōhutukawa (Metrosideros excelsa) and rātā (Metrosideros spp.), and other native myrtaceous that are fundamental to Māori culture, language, identity, and intergenerational narrative and history (Teulon et al., 2015; Black et al., 2019). Additionally, myrtle rust has the potential to have severe economic impacts on plant nurseries, forestry, and horticulture (Beresford et al., 2019).

Surveillance is fundamental for the management of plant pathogens and the diseases they cause (Parnell et al., 2017; Carvajal-Yepes et al., 2019). Surveillance comprises the system of tools and techniques that enable increased detection, knowledge, awareness, and reporting of plant pathogens that can inform management actions to prevent or minimise their impacts on host plants and ecosystems. In trying to address kauri dieback and myrtle rust, Māori have struggled in their attempts to collaborate with researchers and government officials, both locally and nationally. This is primarily because the New Zealand biosecurity system engages hapū/iwi well after decisions and prioritisation for resources and funding have been set by government agencies. Rangatira are directed by authorities to seek out “community” values and concerns, but hapū/iwi exert very little influence over the decisions and management methods that are used to protect their taonga.

In addition to the above shortfalls around indigenous engagement, data needed for surveillance planning and implementation are collected and managed by multiple agencies (e.g., government departments, government-funded crown research institutes, universities, and regional councils) which are disconnected from the places (and people) where they originated (Campbell and Teulon, 2018; Bradshaw et al., 2020). Surveillance is often intermittent, irregularly reported, and follows different methodologies scaling through local, regional, and national levels. Challenges for regular, reliable, and systematic data sharing have been created by a history of mistrust between partners, tensions in the protection of cultural heritage, concerns about data mining, and the desire to protect confidential commercial information. Surveillance data, though intended to be shared, is more often “banked” and inaccessible, which limits their long-term usefulness. This creates data integrity issues, with data being duplicated or “lost.” Many kaitiaki and rangatira are concerned that surveillance is currently being delegated to community groups and report a lack of access to data about their sovereign territories, and poor resourcing and funding to produce and curate data. Disadvantaged by these challenges, hapū/iwi are unable to effectively participate in planning and in conducting surveillance that enables kaitiakitanga of their taonga and whenua.

There are significant challenges in ensuring that the inclusion of indigenous people and knowledge into the development of environmental management strategies or research priorities is done equitably (Harmsworth and Awatere, 2013; Lyver et al., 2019). Not all these issues can be solved quickly, but there are several steps that can be followed to begin working towards a more equitable relationship between indigenous and non-indigenous knowledge. In this paper, we present the principles and methodologies of the mātauranga Māori framework for surveillance (MMFS) of plant pathogens, which aims to elevate mana whenua and mātauranga research into the biosecurity and science systems in Aotearoa New Zealand. We first describe how the MMFS creates opportunities for the co-existence of mātauranga and empirical scientific knowledge, and addresses issues around data ownership and sovereignty, informed consent, and cultural licence. We then present a case study where the MMFS has been applied to research initiatives aimed at addressing myrtle rust and kauri dieback in Aotearoa New Zealand. Finally, we describe how the MMFS informed the development of two online tools: the integrated intelligence platform (IIP) and the proof of pathogen absence (POA). The IIP is a data storage platform which anchors data to its place of origin, recognising its provenance and giving effect to Māori data sovereignty. The POA is a tool to co-design with mātauranga and scientific environmental experts a risk-based surveillance plan for the purpose of demonstrating freedom from disease in areas where a pathogen has not been detected. Te Tiriti o Waitangi and WAI262 guided the development of the MMFS, which builds upon both existing and emergent understandings, values, approaches, and opportunities to improve surveillance in Aotearoa New Zealand.

The three principles of the MMFS centre around enabling equitable representation of indigenous and scientific knowledge systems in the development of research initiatives for the surveillance and management of plant pathogens. The principles are: (1) equitable status of knowledge systems; (2) equitable access to data and information; and (3) equitable investment and/or resourcing. We describe these principles below, including methodologies that have been developed to aid the application of these principles.

The IIP² is a user-registered web-based spatial data infrastructure for storing, viewing, mapping, and sharing of spatial data. The key challenge addressed by the IIP is how to practically encode indigenous provenance information and cultural responsibilities into existing and new surveillance data. Within the platform, the sovereignty of data is determined by the place of origin of the taonga, i.e., it is place-based and anchored to a BMA. In practice, any data uploaded onto the IIP is “tagged” as belonging to a given sovereign authority, which is represented by the BMA where the data were collected. During this “tagging,” the tangata kōkiri from that BMA gains access to the data. Accordingly, any user of the IIP can request access to a specific dataset by requesting it from the custodian (who uploaded the data) or from the sovereign authority (who shares ownership of the data and is represented by the tangata kōkiri). The platform establishes common descriptors for the attributes of each BMA (Figure 3), including a field to identify the tangata kōkiri. The BMAs are designed to directly support and benefit hapū/iwi, and to signal that place-based information carries accompanying cultural rights and responsibilities, meaning that appropriate permissions must be sought for future use of that knowledge. By querying which tangata kōkiri is associated with a given BMA, researchers can begin to engage with the chosen hapū by following the appropriate communication channels. The use of the IIP by custodians encourages collaboration with indigenous tribal communities and creates a digital space for indigenous provenance. Data can be easily accessed and contributed by anybody holding surveillance and monitoring data. On the flip side, the platform ensures mana whenua have timely access to up-to-date data collected within their BMA, which is of utmost importance for decision-making (Hudson et al., 2016).

An essential goal of this data repository is to facilitate the discovery of and access to available resources. Such a process relies heavily on the quality of the metadata. The platform adheres to the ANZLIC Metadata Profile³ and defines a minimum set of metadata that must be supplied for spatial datasets and other resources (Figure 4). See Supplementary material for a full description of each metadata attribute. It also defines a minimum set of attributes constructed from the Darwin Core⁴ open standard to link biologically and ecologically important metadata with downstream data products. Furthermore, the platform allows custodians to input information about the contribution of Māori to the design and implementation of the project. For example, one metadata field allows custodians to indicate whether there is consent in place from the indigenous community for collection of the data (in the form of a signed CAA) and signal their level of engagement with hapū/iwi.

Digital field surveillance forms⁵ enable trained kaitiaki to undertake monitoring of myrtle rust and kauri dieback to track their impact on plants and ecosystems over time, ensuring that the same data are consistently being collected by different observers. Both myrtle rust and kauri dieback field collection forms have been co-developed with kaitiaki and linked to online apps, collecting data via web or mobile devices, and defining a minimum number of attributes that need to be collected, many of which have predefined options. Collecting the same data from both infected and uninfected plants and the surrounding environment, and across data contributors will mean that in the future, data from different custodians will be comparable. This will provide a better understanding of the impact and severity of plant pathogens across BMAs and nationally. The key principles behind storing surveillance data on the IIP are transparency and confidence in the data-sharing obligations, and the opportunity for mana whenua authorities to review and approve research involving Māori-centric data. As such, the platform is a mechanism to capture both bodies of knowledge in one place and enables a reconciliation of information to support surveillance and monitoring efforts.

The MMFS widens the focus of the surveillance practice to include the environment, pathogen, and host, as opposed to mainly focusing on the pathogen or disease (Figure 2). By tapping into the detailed, inherent, and unique knowledge of local biodiversity and ecosystems held by kaitiaki, changes in the wellness/illness of the environment and taonga can be recognised and investigated further to confirm whether they indicate presence/absence of disease and/or pathogens. If pathogen presence is suspected, a surveillance plan is needed to confirm or deny this. However, the lack of pathogen detection during surveillance efforts in an area of interest is not equivalent to pathogen absence, but it does provide some confidence in its absence. This confidence will vary with the intensity of surveillance that is conducted, the risk of spread from known infestations, and the presence of environmental factors influencing the vulnerability to the pathogen (Bradshaw et al., 2020; Sutherland et al., 2020). The more we search for a pathogen and do not find it, the more confident we can be that it is not present. The proof of pathogen absence modelling quantifies this confidence into a probability of absence (PoA; Anderson et al., 2013).

The proof of pathogen absence modelling approach superimposes a grid-cell system over the area of interest. The grid cell is the fundamental surveillance unit, i.e., the aim is to detect whether the pathogen is present in a grid cell. Given no detection of the pathogen in the area of interest, our level of confidence in pathogen absence depends on: (1) our confidence that the targeted area is free from the pathogen before doing any surveillance (for example, as evidenced from the health of the ecosystem); (2) the level of effort that is spent in finding the pathogen; and (3) the probability of detecting the pathogen if it is present in the targeted area (system sensitivity). The first quantity is called the “prior” and is specified as a probability distribution (Anderson et al., 2013). This prior is then updated with the no-detection surveillance data to produce the posterior PoA. If the calculated PoA is not high enough, then more surveillance needs to be conducted (thus increasing system sensitivity) until an acceptable value of PoA is reached. It is statistically impossible to achieve PoA = 1, so the level of confidence needed to declare that the targeted area is free from the pathogen (i.e., the target PoA) becomes a management decision. The target PoA value must be chosen so that the risk of incorrectly declaring an area free from the pathogen is balanced against the expense of additional surveillance activities incurred to achieve a higher PoA (Gormley et al., 2018). Establishing a target PoA and a quantitative mechanism for estimating effort required to achieve it helps guide decisions and resource allocations and creates consistent goals and expectations among local surveillance experts, managers, and policy makers.

Specifying the prior requires on-going discussions among local mana whenua and kaitiaki, plant pathologists, modelling and surveillance experts. The prior can be obtained using the following: (1) information from previous surveillance programmes set up to locate infection and the extent of the infection; (2) statistical forecasts of pathogen distribution; (3) mātauranga Māori and expert opinion/judgement/observations; or (4) a combined approach of the previous options – essentially using mātauranga Māori and expert opinion/judgement/observations, but informed by knowledge from previous surveillance programmes, forecast of pathogen distribution and other factors. In this way, this Bayesian framework provides a mechanism by which both mātauranga Māori and empirical scientific knowledge can be equitably adopted into the proof of pathogen absence model and used to map areas free of the pathogen.

The proof of pathogen absence model is intended to assist in the design of risk-based surveillance for the purpose of demonstrating freedom from disease in areas where the pathogen has not been detected or delimiting the disease front in areas known to be infected. Risk-based surveillance is an approach to disease surveillance that involves looking for disease where it is more likely to be present. At the heart of risk-based surveillance and proof of absence modelling is therefore an understanding of risk factors and their impact on disease and pathogen distribution. However, the paucity of data presents a major constraint in the design of risk-based surveillance in the plant disease context. In particular, the areas where more information is required for kauri dieback and myrtle rust include: (1) quantitative evidence of the risk factors influencing pathogen occurrence; (2) estimates of the sensitivity of diagnostic tests used to detect pathogen presence; and (3) data on prevalence of infection for different plant species and locations. At present, the only feasible approach to design kauri dieback and myrtle rust risk-based surveillance programmes that are specific to each BMA appears to be consultation with mana whenua and kaitiaki, surveillance experts and plant pathologists. The approach is currently being trialled and co-designed with mana whenua from three BMAs with kauri forests. The data obtained will allow us to refine the proof of pathogen absence model assumptions and parameters and fill some of the existing data gaps. This will have benefits not only for efficient surveillance but for disease control more generally.

The increasing threat of invading pathogens that affect taonga species in Aotearoa New Zealand creates new challenges in designing surveillance approaches that can provide sustainable, and socially and culturally just outcomes. Strategies are needed that empower the role of hapū/iwi as kaitiaki of their taonga. In this article, we describe the MMFS, an approach in which indigenous and empirical science systems generate different manifestations of valid and useful knowledge that contribute to innovate and support the discovery, surveillance, and management of plant pathogens; and to achieve positive biodiversity and ecological outcomes (Black et al., 2019).

Using kauri dieback and myrtle rust as case studies, we have presented how the MMFS ensures that hapū/iwi are elevated into the biosecurity system, and mātauranga Māori into the science system. More generally, the MMFS articulates a way of looking at environmental surveillance that can be applied to the full range of environmental problems and to indigenous populations within Aotearoa New Zealand and internationally. The approach consists of three principles. First, it acknowledges that both indigenous and empirical scientific approaches and perspectives have their strengths and can complement each other, and therefore should be considered and attributed equitable value in environmental surveillance systems. Second, it recognises and gives effect to the sovereignty of the data required for the surveillance of plant pathogens and environmental monitoring. Key to the MMFS is the use of BMAs, which allow indigenous tribes to be directly connected with data generated by various custodians and provide a practical mechanism to digitally integrate data provenance and cultural licence into research practice and data collection, use and storage. Third, it recognises that hapū/iwi require equitable resourcing and/or funding to engage in surveillance, monitoring, and management of plant pathogens.

The MMFS seeks to provide benefits for Aotearoa New Zealand biosecurity and science systems through several tangible outcomes. First, a stronger cooperative and collaborative local and national approach to surveillance driven by partnerships between mana whenua and central, regional, and local organisations. Second, a better understanding of the current and emerging capability gaps for mana whenua involved in surveillance. Third, the development of a data storage platform which anchors data to the place of origin and ensures improved information standards, resulting in more robust and credible information on Aotearoa New Zealand’s plant health and pathogen distribution. Finally, a “proof of pathogen absence” tool, which assists in the design of risk-based surveillance for the purpose of demonstrating freedom from disease in areas where the pathogen has not been detected. We have argued that the adoption of indigenous knowledge and practices such as kaitiakitanga, whanaungatanga, and rangatiratanga, and the empowered engagement of indigenous environmental resource managers and their hapū/iwi are vital for the sustainable management and long-term protection of kauri ecosystems and Myrtaceae species across Aotearoa New Zealand. Such a collaborative approach provides efficiencies in national, regional, and local biosecurity strategies and tactics and, importantly, enables the fulfilment of indigenous aspirations of spiritual, economic, environmental, and cultural wellbeing as well as engagement of rangatira and kaitiaki into Aotearoa New Zealand’s biosecurity and science systems.

The original contributions presented in this study are included in this article/Supplementary material, further inquiries can be directed to the corresponding author.

WW: Conceptualization, Funding acquisition, Investigation, Methodology, Project administration, Writing – original draft, Writing – review & editing. AL: Conceptualization, Investigation, Methodology, Writing – original draft, Writing – review & editing. ML: Funding acquisition, Methodology, Project administration, Supervision, Writing – review & editing. DA: Conceptualization, Funding acquisition, Methodology, Supervision, Writing – original draft, Writing – review & editing.