Community conservation data in New Zealand

3 February 2018 | #article#university#featured#conservation

For my 2017 honours year in geography I decided to focus my dissertation on the data supporting community conservation, with the goal of understanding it better and then being able to make some suggestions for improvements.

The following is a summarised adaptation of my dissertation. The fully-referenced document including the individual write-ups for the six interviewed groups can be found at the end of the page.

A trap box One of Friend’s of Rotoiti’s pest traps in the Nelson Lakes National Park


Introduction

New Zealanders are fortunate to live in a place of much biodiversity, and over 600 community conservation groups work to help improve the state of the environment through restoration and conservation efforts. The existence of these community conservation groups can be attributed to environmental, economic and social factors including declining biodiversity, ongoing underfunding of the agencies tasked with protecting the environment and the increasing ‘conservation conscience’ among the general public. The work undertaken by these groups is diverse and includes practical work, such as pest trapping, species monitoring, tree plantings and weed control; and legal work, such as defending the environment in court. In order to support these activities, many groups collect data and information, mostly about the direct work they do but also on their desired outcomes. Because of the diversity in the work undertaken, it follows that the data that are being collected will vary significantly in type, collection, method, storage and distribution.

Other studies have looked into community-based environmental monitoring in New Zealand, and have suggested that better management of data could lead to better conservation outcomes, but they do not examine the processes by which groups presently manage their data. Therefore, exploring community conservation groups’ data management practices is a good area for further research.

Background: Benefits of sharing and connecting data

Considerable research has been done showing the benefits to both sharing data, and connecting disparate biodiversity data. Therefore, once more is known about community conservation groups’ existing data, a logical next step would be to see whether more value could be obtained through these practices.

Benefits of increased biodiversity data sharing include the ability to:

  • integrate with regional and national databases to provide a more complete picture of biodiversity nationally (assuming common standards for comparability)
  • provide more robust knowledge on the circumstances and location under which certain monitored species are thriving, in turn contributing to national understanding of biodiversity trends

However, simply sharing biodiversity data doesn’t necessarily help—it needs to be able to be used effectively. In order to gain a better understanding of the data in a wider context, it is necessary to not only collate it, but also provide the means to link it together in a consistent manner, especially given the increasing volume of information that is available.

Many technical, social and practical barriers exist to improved data sharing and connectivity, including:

  • competing approaches to how biodiversity information can be linked (e.g. Darwin Core, JSON-LD)
  • the reluctance of researchers to share information
  • ensuring quality in public biodiversity databases
  • the fact that databases are often designed/customised to suit the needs of their communities

However, whilst not without its challenges, the consensus across articles studied is that improved sharing practices along with the better linking of data will lead to an enhanced understanding of biodiversity. Hence, combining this knowledge with research into community-collected data should lead to a better understanding of whether more value can be obtained.

Research aim

The aim of this research is to first determine what sort of data are presently being collected by community conservation groups, and how they are currently managing it. Secondly, given that previous research suggests there are benefits in sharing and connecting data, this research aims to look at whether more value can be obtained from this community-collected data using these practices. Six research questions were developed to guide the research, covering current practices (storage, collecting, use, sharing), as well as benefits and barriers to sharing/connecting.

Methodology

This research used a series of semi-structured interviews to develop a set of six case studies, complemented with a review of local and international literature covering the technical, social and practical aspects of conservation data and sharing. Broadly, this approach was chosen in order to develop an in-depth understanding of groups’ practices with data, rather than undertaking a broad overview study similar to previously undertaken research on community conservation.

Semi-structured interviews were chosen over questionnaires because they allow for a flexible and in-depth approach to getting information. These were used to develop case studies, a widely used approach based on the notion that studying a few instances of a phenomenon can help with understanding the wider situation. They also allow for the discovery of unexpected and unusual information.

A simple qualitative analysis was undertaken, whereby information was classified into categories consistent with the research and interview questions.

Within this framework, this research involved writing up six case studies based mostly off interviews with members of conservation groups from the Canterbury and Nelson/Tasman regions. Fifteen questions were used to guide the interviews, covering background information, current practices with regards to data and opinions on improving data availability. Following write-up, a summary table was created enabling practical and technical themes across case studies to be determined. Finally, the information obtained through the case studies and summary table was then extended with literature to explore these themes and provide guidance on how data can be better used.

Individuals/groups interviewed

  • Graeme Kates, Arthur’s Pass Wildlife Trust
  • Peter Hale & Wayne Sowman, Friends of Rotoiti
  • Gwen Struik, Friends of Nelson Haven & Tasman Bay
  • Ruth Bollongino, Project Janszoon
  • Alistair Sheat, Abel Tasman Birdsong Trust
  • Ian McLennan, Ōtamahua/Quail Island Ecological Restoration Trust

Map of NZ showing approximate location of groups Approximate location of the community groups interviewed. Base map courtesy Geographx (2009).

Limitations

There were a few limitations associated with this methodology. The first related to the selection of interviewees, with all interviewed groups being based in the South Island. This was ultimately due to their availability and accessibility to be interviewed, but ideally the research would have included a more broad range of groups in different geographical settings given the diversity of environmental challenges around New Zealand.

Another aspect to consider was the effect of personal subjectivity and bias, that is, how my worldview might influence results (positionality). For example, what I considered to be relevant and interesting during the interviews may not have been seen as such by a different researcher. Recognising positionality doesn’t invalidate research, rather it simply means being aware of how my position and knowledge might influence results.

A further limitation is that the use of a case study based methodology means that whilst a depth of knowledge can be obtained, it can often be lost through the simplification necessary to analyse and make comparisons. Case studies aren’t always able to be ‘generalised’ (applicable in other instances), however they are able to surface new and interesting information that might have been missed through a survey. To try and get the best of both worlds, this research presented the case studies in full, but also used a summary table to draw comparisons.

Results

Background and context

The case studies represented a variety of different situations:

  • Three of the groups worked in a coastal environment; two in an alpine environment and one on an island.
  • Five of the six groups were more ‘active’ environmental groups, i.e. taking direct action to restore the environment; one of the groups was mainly ‘reactive’, i.e. responding to threats to the environment via legal means.
  • All groups were registered charities (and funded by individual donations to a greater or lesser extent), but only one had ongoing major financial backing. Other funding sources included support from local authorities, grants from legal funds, funding from commercial operators working in the area and one-off grants for specific projects/species.

Types of data

Types of data collected included:

  • Outputs/operational: the direct results of work done. The most common data of this type related to pest trapping, i.e. information about traps, species caught, catch rates, baits and issues.
  • Outcomes monitoring: measuring the effects of environmental restoration on species. This included bird sightings (both formal surveys & citizen science), species specific data (e.g. relating to kiwi or whio), vegetation surveys, or photographs (documenting change over time).
  • As-needed data: data collected to support a specific activity (e.g. court cases).

Two of the groups conducted little outcomes monitoring themselves, due to their strong working relationship with DOC or other groups working in the area.

Reasons for collection

Reasons for collection varied, but included:

  • Supporting operations, e.g. trap data.
  • Measuring progress against specific restoration plans/targets.
  • Assisting with funding applications, that is, giving an indication of the work being achieved.
  • Improving general knowledge and understanding of ecological relationships and species interactions (hopefully assisting other projects).
  • Supporting court cases: both sides in court are often required to collect environmental data to support their case, though the information is not necessarily objective.

Collection methods

Collection methods included:

  • Paper: by far the most dominant method of collecting data for all activities.
  • Apps: one group used ‘Walk The Line’ for collecting trapping information, another had a custom built app for the national park they operate in.
  • Photos: both on film (historical) and digitally.

Most data were collected by regular volunteers or staff/contractors, but one group reported citizen science as being a part of their data collection.

In most instances data collected in the field on paper was then entered into a database, spreadsheet or website. However, some groups preferred volunteers to enter the information into these systems themselves (reducing double-handling and encouraging ownership), whereas others used a designated person to enter data (meaning more oversight and less likelihood for error, especially if paper records were collated in one place for verification). In at least one instance, data were simply kept on paper because of the low volume of information.

Storage methods

There was much variation in the storage methods across groups. For example, for trap data alone, storage methods included paper, a customised website and the Department of Conservation’s (DOC) internal systems.

Techniques for storing digital data included:

  • Excel spreadsheets
  • Access databases
  • eBird (global citizen science website)
  • Google Drive
  • Files on personal computers

Physical data (i.e. paper) was found to be stored both on site, at volunteers’ homes and in one case at the local museum.

In some instances data were duplicated in multiple locations. For example, in one instance a group stored trap data in their own systems but also had to manually transfer it into DOC systems. In other instances, paper records used to collect data were stored in addition to being entered into a database for verification.

Where scientists or consultants wrote up scientific/evidential reports, the storage of the data was often up to the individual, with only the written report being made available.

Data use

Data collected was used for:

  • Informing decision making: e.g. responding to predator spikes (rapid increase in catch numbers), informing where future trap-lines might go and deciding whether to undertake landscape-scale pest control by DOC
  • Creating reports: e.g. graphs/maps showing numbers of pests killed, reports for funding applications, mapping locations of plant pests, etc.
  • Monitoring the effectiveness of restoration efforts: e.g. adaptive management (regular reviewing of data to ensure work is effective, and adjusting if not), determining ‘hot’ (high catch) and ‘cold’ (no catch) traps, and also measuring efforts against a long-term strategy/plan.
  • Creating scientific papers/consultant reports: e.g. a paper on lessons learnt with pest control, evidential reports in court cases

Current data sharing

All groups shared knowledge by some means, but what was shared and how it was shared varied:

  • Only one group specifically shared raw data by default through their customised website.
  • Four groups shared data with DOC by virtue of using their systems for storing information (mostly trapping data)
  • Two groups had access to each other’s data through DOC’s systems because they work in the same national park
  • At least one group loaded information into eBird, which meant the data was available to others

Screenshot from the APWT website The Arthur’s Pass Wildlife Trust online database, with an example of its graphing capability

Whilst not data sharing per se, there were multiple examples of ‘knowledge sharing’ across groups:

  • More groups had a newsletter or similar to inform volunteers and supporters
  • There was one example of a ‘shared’ newsletter, the Nelson/Tasman Conservation Volunteers, which compiled news from over twelve local conservation groups
  • Some groups published reports on their websites
  • When environmental information was collected for court cases, this was often made public as part of court processes

When asked about whether data would be provided on request, all groups indicated a willingness to share information within reason, however one interviewee said that they would rather work with the person to ensure they had relevant context for the data.

Opinions: Benefit of sharing

All interview participants saw some benefit to data sharing:

  • Data sharing was seen as a useful tool for groups operating in the same region, because the effects of environmental restoration and predator control are likely to impact on surrounding areas
  • One participant suggested that sharing data in an area was useful to get a better understanding of the restoration efforts for a wide area
  • Another participant said that making raw data available allows anyone to verify interpretations of the data

Some reservations were expressed:

  • One participant was wary about the potential for over-interpretation, and also drawing conclusions from data without having the necessary explanatory context
  • Another participant saw little value in sharing information about trap catches, beyond simply showing the scale of the problem

Five of the six interviewees said that information sharing was of equal, if not more importance than simply sharing raw data. Suggested information could include successes, failures and lessons learnt; learning and networking events; conservation-related news and new techniques for pest control.

Opinions: Issues/barriers to sharing

Many issues were highlighted as being barriers to sharing data:

  • Social issues: data ownership (especially with multiple contributors), data sensitivity (not all data are appropriate to publish), buy-in of systems (motivation of people to use and continue to use a system), reluctance of people wanting to share data (e.g. due to concerns about interpretations of data)
  • Practical issues: funding (insufficient or short-term), organisation (e.g. fragmentation of current data sources), resourcing (having access to suitably trained people to interpret data)
  • Technical issues: data flexibility (customisation to capture necessary data over time vs. rigidity for comparability), security and management

Key comments

Using a semi-structured interview approach allowed for the capturing of kea comments from each of the interviews:

  • Kates (Arthur’s Pass Wildlife Trust) mentioned the incompatibility between a lot of the current conservation databases that exist: “There are a lot of databases out there that all want some form of the data [the community group collects]. None of [the databases] seem to communicate between themselves”.
  • Hale & Sowman (Friends of Rotoiti) highlighted on a number of occasions that “people keep re-inventing the wheel… it is all about communication and information sharing”, referring to the lack of collaboration between community groups about successes, failures and lessons.
  • Struik (Friends of Nelson Haven & Tasman Bay) stated that most of the information of coastlines at the top of the South Island was due to court hearings on environmental cases that require the collection of data by both sides of the court case, in order to understand the environmental effects. She also stated that any information or data that can help with court cases is beneficial to be shared.
  • Bollongino (Project Janszoon) emphasised that “the collection and storage of data is not the limiting factor… it is the lack of the ability to have the data analysed properly”. She also said that having a forum for exchanging experiences and lessons would be helpful, and that buy-in issues would be mitigated as more young (and hence technically able) people get involved.
  • Sheat (Abel Tasman Birdsong Trust) referred to the necessity for providing context when undertaking study of datasets: “context is everything”. This is because ecosystems are very complex with many variables, and that it would be easy to draw incorrect conclusions just looking at numbers alone. He also thought it would be useful to visually map the extent of all conservation groups, so people in groups could easily see other groups and activities in a particular area.
  • McLennan (Ōtamahua/Quail Island Ecological Restoration Trust) said that it would be useful to have access to people with GIS ability to assist with map-making. He also highlighted that there are already presently a lot of ‘umbrella’ organisations seeking to work across conservation groups, and that there needs to be caution about introducing more entities of a similar ilk.

Discussion/Recommendations

Using the research questions as guidance, a number of themes were determined from the case studies and enhanced with literature:

Resolving barriers to data sharing

As mentioned, most groups saw some benefit to sharing data, especially on a regional basis. However, some issues were pointed out, including buy-in, ownership, the reluctance to share data and data sensitivity. Additionally, little value was seen in sharing outputs data (e.g. trap catches) beyond simply showing the scale of the problem.

Existing literature discusses some of the ways that these issues can be mitigated. For example, one paper states that data entry into systems needs to be incentivised, as it can often be the last thing volunteers want to do after being in the field. An example of an incentive would be if the database was able to provide immediate and interesting feedback on results just entered, such as looking at trends over time or differences amongst sites.

Data ownership was another key issue, especially where the information has been collected by many people over time. To resolve this problem, it should be made clear who owns the data from the outset, especially when it might be stored on DOC’s systems as is the case for many of the interviewed groups. Having a clear definition of the owner gives the owner options as to future uses of the data, such as publishing, licensing or sharing the information. One group reported having a ‘gentlemen’s agreement’ with DOC to use their systems to store data they collect, but this should be formalised to ensure longevity of access to data in the unlikely possibility of a future dispute.

At least one interviewee expressed reluctance about sharing data because of its potential to be misinterpreted without adequate context. In a major study into the obstacles to data sharing, the authors found that this reluctance was a common reason cited for not wanting to share data. However, as a solution, the authors simply suggest that researchers must accept that they will not able to maintain control over their data forever, otherwise it will be ultimately lost. Ensuring that data when published has adequate guidelines and context would also help mitigate this issue.

Regarding data sensitivity, one paper studied suggested that when data sensitivity is an issue that the data be generalised so it is still sharable in public, but without enough detail for potential misuse. Alternatively, they suggest that data sensitivity might decline over time, meaning that datasets could eventually be published to assist with future work.

Whilst not a point raised in the case studies, one paper also mentioned that some clarity around ‘data sharing’ versus ‘data publication’ is necessary. The authors argue that data used to support a scientific paper should be published rather than simply shared, as sharing suggests a negotiation between parties on the use of the data whereas publication guarantees data availability. This distinction is perhaps less relevant for the ongoing collection of community conservation data where there is no finite end-date for ‘publication’.

Data management

Data management practices varied significantly across groups, however despite this it appears that groups were able to find a workable solution for managing their outputs data—that is, the collection and storage of data was not impinging on their ability to undertake their work. However, it is still worth evaluating their efficacy to see whether the data can be managed better, especially with regards to sharing.

Four groups reported using DOC’s internal systems for storing information, such as relating to traps. It appears that DOC systems are used for the sake of simplicity. These systems typically are accessible to DOC staff only (requiring a DOC login), with groups accessing it through staff who are also members. This system, whilst workable, is not ideal in that the data are constrained to the way DOC handles their data, and its availability is dependent on their access policies, which may be more restrictive than those of other more public systems. Ideally, data collected by community groups should be available at least to all of the people who contribute it, through a more outwards-facing system. However, a long term goal might be for DOC itself to share more of the (non-sensitive) information they collect, given the benefits of sharing data.

Using established public-facing systems, such as the citizen science platform iNaturalist NZ or sharing with the Global Biodiversity Information System (GBIF) would also have the effect of complementing collected data with existing data from others. There are many existing systems available covering species nomenclature, environmental data, genetics, vegetation plots, and species distribution. Citizen-science systems such as iNaturalist NZ also allow for the peer review and moderation of data by experts to ensure its quality, a necessary step for the usefulness of any biodiversity resource.

In any case, with every system it is crucial to ensure that there is buy-in from the people that are meant to use it, especially when moving from a physical/paper-based system to a digital system. Ensuring there is adequate support from the outset for less-technical conservation volunteers, or alternatively having designated data entry people can help with this. However, as one interviewee suggested, this might be less of a problem over time as more (generally younger) digital-savvy people get involved in community conservation.

Knowledge sharing

As mentioned, when asked about data sharing, most interviewees said that sharing knowledge was of equal, if not more importance to sharing data. Knowledge sharing, as in the sharing of successes, failures and lessons learnt, was especially highlighted by one interviewee who emphasised that “people keep re-inventing the wheel… it is all about communication and information sharing”.

Services already exist to facilitate this to some extent, such as the website ‘Nature Space’ run by a governance board with representatives from DOC and other environmental groups. However, only three of the six interviewed groups were on the system, and none of the interviewees reported knowing anything more about the service other than recognising they were part of it. This suggests that the system is not presently facilitating knowledge sharing particularly well due to lack of awareness. With technical solutions to information sharing being well established, raising awareness of a system such as Nature Space, and understanding what people would want to get from such a system is crucial to it being a success. This is corroborated by other research that suggests that the user satisfaction, i.e. that they are getting value from a system, is the key determinant of continued usage for IT systems.

It is important to note that websites are not the only way by which sharing can take place. Forums, workshops and collaborative events represent another way to share knowledge, but also a simple approach such as a regional newsletter can also be beneficial. This is the case in the Top of the South region, where a volunteer compiles news from over twelve conservation groups in the Nelson/Tasman area, including noteworthy news, events/workshops, trap statistics and lessons learnt. This newsletter is distributed via email around the respective groups and interested individuals, and is proving to be a simple but effective way of facilitating more knowledge sharing. One interview participant also suggested that maintaining a map of the working areas of conservation groups would help other groups to realise what other work is being done in the region, and potentially facilitate community building.

Discoverability and the necessity for a coherent source of community conservation information

One issue noticed from the start of this research was the lack of definitive information on community conservation groups. DOC has a list of about 200 groups on their website, but this falls well short of the 600 figure stated by one study of New Zealand conservation groups monitoring methods. The authors of this study had to resort to using eight different databases to compile their list of groups to contact, three of which were non-public databases accessed with permission. This scattered information means simply trying to make contact with community conservation groups across the country is problematic.

Similarly, for community groups themselves there is no single source of information to help support their activities. For example, if a group wanted to know more about starting a pest trapping exercise there is information available on over four websites including the Predator Free New Zealand Trust, Nature Space, Kiwis For Kiwi and the National Pest Controls agency. The Nature Space web page on trapping simply provides a list of links to other websites, and trying to distil the relevant information and latest best practices is difficult with so many sources of information, especially for volunteer-based groups who may not have the time or expertise to figure it out.

Monitoring toolkits have been created for community groups, with the intention of making science, such as species monitoring, more accessible to those with no formal science. One study found that whilst volunteers who used the toolkits reported their success in providing robust monitoring data, very few groups used them which suggests a lack of knowledge about available toolkits. It appears that a lack of information is not the hindering factor for groups, rather it is issues with discoverability, that is, finding the relevant information.

In essence, the problem requiring solving is distilling what is or is not pertinent to community groups, and making sure that information gets to the relevant people. This was a point made by one interviewee who said that sharing information and making sure it is getting to the ‘right people’ was more important than just simply sharing data. Having a complete list of community conservation groups would also help the groups themselves understand who else is doing similar work in their region.

Resolving this issue requires different stakeholders, including government bodies, scientific entities and charitable trusts, to work together to reduce duplication and provide a definitive source of information for community groups seeking to undertake conservation projects and biodiversity monitoring. If these resources are consolidated, the resultant website would also need to be actively maintained as practices change, and awareness-raising efforts should be made to ensure buy-in from community groups. However, as stated by one interview participant, any such outcome should be done through an existing entity or project, as they said there are already a number of ‘umbrella’ organisations out there seeking to work across community groups, and they would be wary of introducing another one. As previously discussed, the site should also have the ability for community groups themselves to contribute and share knowledge as they find solutions to problems, such as one group did with designing a ‘mouse excluder’ for traps.

Access to funding and resources

As discussed, the lack of funding is a typical issue for conservation, especially with regards to ongoing funds, hence it is an important factor to consider for data management. Five of the six case studies did not have a source of ongoing funding, relying on donations and charitable grants to sustain their activities. Unreliable funding can be problematic for data collection, especially for long-term datasets. Many systems have been built using a one-off grant from the (former) Terrestrial and Freshwater Biodiversity Information System fund, however without ongoing support a lot of the effort expended on developing systems was useless.

However, as suggested by one prominent scientist in the field, it can be argued that funding itself is not the main barrier to assisting community conservation groups with data, rather it is a lack of commitment from government entities, tertiary institutes and CRIs to take responsibility and work together to support community groups. This view was backed by two community groups, who stated that if a new system was built to help with community conservation, it would have to be adequately resourced to be successful into the future.

Another issue related to resourcing was groups not having access to people with the knowledge to interpret collected data. At least two of the groups had committee or staff members with a career background in science, which meant that those individuals were able to perform analysis of data to gain additional meaning from it. However, access to the personnel with the right skills is intermittent as it simply depends on whether there is someone with the appropriate background involved with the group. One interviewee suggested that this lack of access to have data analysed was more of a limiting factor than issues with data storage and sharing. Ideally, community groups would be able to access expertise relating to statistical analysis and GIS.

Overall, access to funding is intermittent and can impinge on the ability of community conservation groups to manage long-term datasets. This can be mitigated if government entities, tertiary institutes and CRIs work together to determine who has responsibility for maintaining community collected biodiversity datasets. Access to analysis is not an issue unique to community groups—as expressed by one interviewee the ability to have more data analysed would be useful for DOC staff as well. Whilst a difficult issue to resolve without funding, if the data was made available to tertiary institutes it might be possible for it to be analysed by students in relevant disciplines.

Data storage and publishing

According to one paper, most ecological data used for scientific research are not accessible after the analyses have been published, which is problematic for both independently verifying analyses, and also potentially gaining new insight from the data collected. The paper states that often the data collected simply remains with those who collected it, for reasons including cost, sensitivity, organisation and ownership. This evaluation is consistent with two case studies, in which the groups had reports and scientific/consultant papers written up, without having access to the raw data underlying their analyses.

Another similarly related issue is the storage of data—many groups reported that the data collected was scattered across different locations, including volunteers’ homes and personal computers. In one example, one of the key comments made by an interviewee was that most of the knowledge on coastlines at the Top of the South had come out of environmental court cases fought by them. However, there was no coherent source for this information, let alone raw data, with information being published in various scientific and consultant reports, and also stored in file boxes at a local museum. In other groups, interview participants reported data being stored by the scientists who were doing the analyses.

The issue of data publishing is not a simple one to resolve, but simply being made aware of the benefits of publishing to the wider science community is a first step. In one paper, the researchers state that putting the effort in to publish data is simply the “right thing to do for science” and can also lead to increased visibility of the work being done. They also state the special importance of publishing collected data for conservation, so assuming that the person collecting the data is doing so to assist with conservation, it would seem logical to also publish the data. However, in some regards, issues with data storage simply related to disorganisation, especially with conservation groups that have been around for decades.

Sustainability of databases

With the rapid pace of technological change nowadays, websites and online databases require active and ongoing maintenance in order to be secure, reliable, resilient, available and easy-to-use. As such, it is important to consider the sustainability of these systems into the future, especially if they’re meant to handle long-term datasets, as is often the case with biodiversity information.

Two of the case studies reported using a customised mobile application or database for the storage of their information. One group had a customised website, designed and maintained by the interview participant, and over time it has been built to contain all of the information required to support the community group’s output and outcomes monitoring. It has data sharing built in by default, and excellent buy-in where all volunteers use the system to store the information they collect. Similarly, another group has a customised mobile application targeted at visitors to the national park they operate in, which allows for the reporting of native and pest species sightings.

However, one of the issues with a customised approach is that the systems require ongoing support to be sustainable in the long term. For the group that has the well-functioning online database, whilst the database works well presently, the question remains over what will happen both to the website and the data it contains when the current maintainer is no longer able to maintain it. Similarly, in the case of another group, mobile applications must be continually updated as the mobile phones themselves are updated. In that particular instance, the group is set to be well-funded for thirty years and presumably able to afford the upkeep during that time, but like the customised website, due consideration must be given to what happens to the app and data in the long term.

The issue of database sustainability has been discussed at length by other researchers who advise that in order to ensure longevity, data should be integrated with larger collaborative databases, and also be owned or managed by an organisation, society or similar with a suitable mandate. In the context of community conservation data, this could be DOC itself, or potentially a tertiary institute or crown research institute. A similar conclusion was reached in a report on citizen science biodiversity monitoring, which recommended the use of a resilient, standardised framework to ensure longevity, especially as personnel involved change over time.

An example of a long-term database meeting the guidelines suggested by one paper is iNaturalist NZ, which is a nationwide citizen science database, using an established underlying system and with its longevity supported by a charitable trust. Using a nationwide database such as this also has the advantage of ensuring commonality, so that information can be compared across different groups and projects.

Another study, lists some of the many well-established databases available for publishing data, such as the Global Biodiversity Information Facility (GBIF). A different paper also lists some of the many established solutions to collecting and storing trapping (outputs) data, including CatchIT and Walk the Line.

Overall, it is important to consider the sustainability of databases when storing data, to ensure that datasets are available in the long-term, especially if a project does not have ongoing funding. For community conservation groups looking to start or expand monitoring programmes, it is recommended that all steps should be taken to use an existing system before considering creating a new one. If there is no other option but to create a new or customised system, then due consideration should be given to its longevity, especially with regards to funding, and it should adhere to already defined standards, such as Darwin Core.

Incompatibility between systems

One of the key comments made by one interviewee was “there are a lot of databases out there that all want some form of the data [the group collects]”. In this instance, some data relating to whio (endemic blue duck) was being collected and stored in the group’s customised database, however DOC also required that the information was stored in their database as well. The two systems are reported to be entirely incompatible, with past attempts to automate the data transfer being unsuccessful, meaning that data has to be manually transferred with extra identifiers added to facilitate the process. Part of the reason the two databases exist is that they meet different needs—one is DOC’s internal-facing whio-specific database, and the other is the publicly available customised site for the conservation group. According to research, it is often the case whereby different data providers exist in order to cater for their own specific users.

This subject of database incompatibility is not unique to community conservation groups, and technical solutions to the issue have been well researched. One example is creating shared identifiers, such as recommended by one researcher, whereby suggestions are made as to how to define globally unique identifiers for biodiversity information, in a similar methodology to how DOI numbers are used for academic referencing. This would ensure data across disparate database systems would be able to be linked. In general, the idea of globally unique identifiers is useful for providing structure across disparate databases.

Adhering to common standards that explicitly define unique identifiers and relationships to other data, such as Darwin Core or JSON-LD, also ensures compatibility amongst databases.

Given that over four pest trapping systems exist, an example of shared identifiers in a community conservation context might be the establishment of a nationwide unique pest trap identifier system, whereby trap data across different databases can be matched up, compared and possibly even consolidated in future.

Future research

Given that this research evaluates some of the issues and potential for community-collected conservation data and makes suggestions, it would make sense to assess their efficacy in the real world. Therefore, future research could involve undertaking small-scale real-world trials with a few community groups to validate the recommendations. The results of these trials, if successful, would provide the grounds to pursue more funding in order to support community groups with their data in monitoring, and hopefully achieve better outcomes for the community groups and the environments they seek to protect.

Conclusion

In summary, over 600 community conservation groups work in New Zealand to help conserve or improve the environment. The work undertaken by these groups is diverse and in order to support these activities, many groups collect data and information. Previous research has looked at objectives and monitoring practices, but has not considered data management practices. Investigating this is especially useful, considering that research suggests there are benefits to the increased sharing and linking of biodiversity datasets.

Through a case-study based methodology, this research looked at the current practices of six groups, including on data sharing already taking place and its perceived value. Themes across case studies were determined and then extended with literature to provide suggestions on improving data management. Themes identified looked at the value of data sharing and knowledge sharing, as well as issues relating to as data storage and information discoverability. The sustainability of systems, and access to resources and funding were also covered.

This research is relevant because the increase in work done by community conservation groups means there is a need to future-proof by improving data management practices. Future research could be conducted through undertaking small-scale real-world trials, to validate some of the many literature-based recommendations, thus providing solid grounds to pursue more funding to support community conservation groups with their data and monitoring efforts.


Reference

Moon, G. (2018). Community conservation data in New Zealand: A review of community-collected conservation data and suggestions for improvement (Honours dissertation). University of Canterbury, Christchurch, New Zealand.

Critical reflection

With the benefit of hindsight and feedback, it would have perhaps been more sensible to conduct this research using a survey/questionnaire rather than the case-study approach used. This was because (a) doing interviews and writing up case studies is very time consuming and (b) the additional level of detail gained from using case studies did not result in an in-depth analysis, mostly due to the time constraints of an honours year dissertation. The case studies are included in full in the appendices of the dissertation, and could always be used again for further research.

Acknowledgements

Thanks to all of the interviewees for their participation and the excellent work they do for conservation. Additionally thanks to Dr. Ben Adams (research supervisor), Dr. Kelly Dombroski (former honours-level coordinator) and Assoc. Prof. Mark Costello (University of Auckland) for their advice and feedback across the year.


This article was updated in March 2019 to reflect the renaming of NatureWatch NZ to iNaturalist NZ