Introduction

Biodiversity continues to decline [1, 2]. There is growing demand for more evidence-based conservation, with data informing decisions and evaluating performance [3, 4]. This will become even more important as the world commits to post-2020 biodiversity targets [5]. In addition to governments and civil society organisations, businesses striving for sustainability also struggle to identify suitable indicators and data sets [6]. Effective, evidence-based biodiversity conservation and natural resource management requires data on the state of species and habitats, the threats and pressures they face, and the policies and actions implemented to address them. However, although monitoring is standard best practice in project management, often it is not conducted thoroughly [7]. As a result, biodiversity data are scattered, fragmented, a challenge to assemble, and rarely available to decision makers [8–10].

Blockages to biodiversity monitoring include lack of access to existing data sets [9], exacerbated by many organisations acting independently to develop their own databases and data platforms [11]. In high-biodiversity countries, such as in tropical Africa, limited capacity and expertise for data sharing and use are often compounded by more limited resources to pay for raw images and data processing, as well as limited internet capacity [9, 12, 13]. Many of the assessments of African biodiversity data have been led and conducted by scientists who are predominantly based outside the region [14, 15], reflecting more systemic issues with capacity for research and monitoring [16–18]. It is therefore perhaps unsurprising that all of the global data sets, and most of the scientists with access and capacity to analyse them, are housed in Europe and North America.

Governments, NGOs and international organisations monitor delivery of global conservation goals, such as the Aichi Targets and the environment-focused Sustainable Development Goals, by using a number of key global databases, such as the IUCN Red List of Threatened Species [19], Protected Planet [20] and the Living Planet Index [21]. The data in these databases can be used to track biodiversity at local, national and global scales [4, 22, 23]. But these databases focus on the state of biodiversity, mostly vertebrates, and on one conservation response (protected areas). What other data are available that could be used by conservation agencies (e.g. government departments, NGOs) and other natural resource managers (e.g. businesses, local communities) at national or international level to enhance biodiversity monitoring?

Only limited efforts have been made to date to identify and share available biodiversity data sources, and these have focused on a single theme, such as threats [24], or one region, such as Europe [11], and they did not target data specifically of use for monitoring. We therefore undertook an inventory of existing global data sets, databases and data platforms, as well as reports that synthesise such data, in order to determine data sources that could help conservationists and natural resource managers monitor biodiversity, especially the state of species and habitats, the threats and pressures they face, and conservation responses. This represents the first attempt to summarise data sources specifically relevant to biodiversity monitoring.

Materials and methods

Data sources and reports were identified through a web search and literature review using a combination of key terms (e.g. biodiversity, conservation, data, data set, database) and terms linked to key threats and actions (e.g. bycatch, deforestation, offtake, pollution). A snowballing technique was used to source other literature from that uncovered. In addition, websites of key organisations working on biodiversity data were explored (e.g. those of the Biodiversity Indicators Partnership, GEOBON, UN agencies such as FAO and UN Environment, and UNEP-WCMC). Similarly, the latest versions of key biodiversity reports were mined for references to specific data sets, especially the Global Biodiversity Outlook, Global Environment Outlook, and assessments of the Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES).

While an effort was made at the start of the assessment to differentiate between data platforms (websites and tools used as portals to access multiple data sets) and other data sources, this proved infeasible, largely because almost all organisations compiling data sources at the global level use data acquired from others. Therefore, throughout the inventory, the term data source is used to cover data sets, databases and data platforms, whether they are primary or secondary sources.

Data sources were included in the inventory if they met the following criteria: potential relevance for monitoring biodiversity state, pressures and responses at the global level by key stakeholders (governments, international organizations, civil society and NGOs, conservation agencies and businesses striving for sustainability); at least some time-series data or plans to collect time-series data; up to date (with data added in at least the last 5years or so). Regional and other sub-global level data sources were excluded. The most useful data sources would have large volumes of widespread data that were scalable, of high quality and regularly updated, but it was not always easy to judge how these criteria were met from the information available. It was also not always easy to assess how accessible data were and if they were free-of-charge. Indeed, even if data are freely accessible they are not always easy to use [24]. Therefore, we note that some data sources in the inventory may still prove challenging for monitoring purposes when investigated in more detail.

Multiple, linked data sets managed by a single agency and consolidated in a single database were considered as one source. For example, the FAO Fisheries and Aquaculture database has numerous data sets (e.g. Global Production, Global Capture Production, Global Tuna Catches by Stock, Global Aquaculture Production, Atlas of Tuna and Billfish Catches, Global Number of Fishers, Consumption of Fish and Fishery Products, etc.) but was counted as one fisheries data source. Similarly, habitat and land cover data were not disaggregated by remote sensing data set but, instead, we identified data sources that consolidated from different sets. For example, forest cover data sources are numerous (e.g. Global Forest Change, Global Forest Watch) but all in turn source their data from a variety of remote sensing programmes, such as ESA’s GlobCover and NASA’s Landsat. The intent was to identify wherever possible pre-prepared data of use to managers, not raw data files for GIS analysis.

Data sources were clustered based on their uses for monitoring biodiversity state, biodiversity threats and pressures, and conservation responses, as per the Pressure-State-Response indicator model widely used in biodiversity conservation monitoring [4, 7, 25]. The data sources that could potentially be used to monitor pressures and responses were clustered under the threats and conservation actions categories developed by IUCN and the Conservation Measures Partnership, CMP [26]. For this exercise, the newer, revised versions of both classifications were used: the CMP Direct Threats Classification (v 2.0 of 2016) and the CMP Conservation Actions Classification (v 2.0 of 2016) [27]. In each case, we developed examples of related indicators and indicator categories associated with each action and each threat and then listed examples of global databases and platforms of potential use in monitoring them. Note that, in some cases, a database could be used for more than one indicator. For example, forest cover data can show the state of the habitat, but a trend in forest cover can also monitor a trend in forest loss, which is a threat. Note too that state metrics–such as species populations trends and habitat cover–can also be used to monitor the impact of various threats (e.g. deforestation rates in relation to infrastructure development or mining).

Results, conclusions and discussion

A total of 145 global data sources were identified of potential value in conservation monitoring (Fig 1): 40 data sources for biodiversity state, with at least 33 open access (S1 Table); 44 data sources for biodiversity pressures and threats, with at least 38 open access (S2 Table); 33 data sources for conservation responses, with at least 28 open access (S3 Table); and 28 data sources that cut across multiple indicator types, with at least 27 open access (S4 Table). Twenty-six types of report were identified (S5 Table) that regularly synthesise biodiversity data from diverse sources. These helped identify some of the data sources. The shortlist of data sources that, from this preliminary analysis, appear to be the most useful in accessing data for monitoring biodiversity were compiled (Table 1).

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Fig 1. Data sources identified.

A summary of the 145 data sources identified by data type, and the proportion known to have at least some data easily (i.e. instantly, openly and freely) accessible.

https://doi.org/10.1371/journal.pone.0242923.g001

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Table 1. Summary of key data sources for monitoring biodiversity and their potential uses for conservation agencies.

https://doi.org/10.1371/journal.pone.0242923.t001

While 86.9 per cent of the data sources allowed instant, open and free access to at least some of their data, the usefulness of that data and the relevance of the formats was not ascertained. The degree to which it was possible to assess what data are available and accessible, the origins of the data, the precise indicators the data measure, and the length of any time series available was very variable and the information was often complicated to find. In some cases, even the organisations managing the data or the websites where data could be located were difficult to identify easily.

Categorising (or clustering) data sources was challenging. Clumping data under broad terms such as “state” was too general, and further subdivisions might be useful (perhaps based on taxa or biomes or geography). On the other hand, the CMP classifications for threats and actions were too detailed to make clustering under each individual action or threat a meaningful (or sometimes feasible) exercise. Once the new post-2020 biodiversity targets have been finalized to replace the Aichi Targets, we will try to cluster some of the data sources under each new target and its associated indicators (sensu [28]) Categorising sources was further complicated by the fact several databases contain multiple data sets (the FAO Fisheries and Aquaculture database being a good example) so can also be listed under several data categories (state, pressures/threats or responses/actions).

Key actors involved in managing data sources of most use to biodiversity monitoring include BirdLife International, the Secretariat of the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES), the UN Food and Agriculture Organisation (FAO), the International Union for Conservation of Nature (IUCN), the US National Oceanic and Atmospheric Administration (NOAA), UN Environment World Conservation Monitoring Centre (UNEP-WCMC), University of British Colombia (the Sea Around Us), Wetlands International, the World Resources Institute (WRI), and the Zoological Society of London (ZSL). This reflects earlier analyses of data sets which noted that a small number of agencies curate most of the data. For example, Joppa et al [24] found six data providers account for more than a fifth of biodiversity threat data sets.

Global data sources exist that are useful in providing time-series data of biodiversity measures such as vertebrate population trends, habitat cover trends, species extinction risk, protected area coverage and management effectiveness, fisheries and climate, though the frequency the data sets are updated varies and there are gaps in taxonomic and geographic coverage. Overall, across data sources, there was better coverage of some biomes, taxa, threats and responses than others. For example, vertebrates (especially large mammals and birds), forests, protected areas, fisheries and certain aspects of climate change (greenhouse gas emissions, sea temperature) are better represented in the data sources than other forms of biodiversity information. There are more data for terrestrial biomes than for marine or freshwater. Even for well-studied taxa like birds, time-series data are mostly from Europe and North America. These findings reflect recognised global trends, with major gaps in biodiversity data in high-biodiversity tropical countries [13, 29, 30]. There are generally more data for Europe and North America than other regions, and more for terrestrial birds, mammals and trees than for other taxa, but there is a lot of local variation [4, 29, 31–34].

There was an uneven spread of databases across CMP pressure categories, with a disproportionately large number for climate change and biological resource use and none that were relevant or easily accessible for energy production & mining and human intrusions & disturbance. For responses, there were numerous data sources relating to livelihood, economic & moral incentives and conservation designation & planning, but none for awareness raising, law enforcement & prosecution, and education & training. There are limited data at global level that allow direct measurement of the benefits and livelihood gains accrued by people due to conservation. This may partly be an issue of lack of data collection [35], but may also reflect the fact local data from site-level projects are not easy to aggregate to regional or global scales.

Only data from satellite-based remote sensing is updated on a daily basis (and therefore provides almost real-time monitoring). WRI’s Global Forest Watch updates information every day on forest loss and active fires. NOAA’s Coral Reef Watch updates data daily on sea temperature, flagging coral reefs where bleaching is most likely.

Some data sources provide access to existing maps (e.g. SEDAC). However, there appears to be a growing trend for organisations to produce portals where people can click on different data sets to make them appear as overlays on a world map (examples include Global Forest Watch, Map X, OBIS-SEAMAP). In most instances, however, mapping has limited use for monitoring, primarily due to the lack of scope to track trends over time in quantifiable ways. It was also often difficult to ascertain how easy it is to access the source data behind the maps.

There are about 15 data sources, with regularly updated time-series data, that were considered to have the most potential for helping conservation agencies with biodiversity monitoring (Table 1). These data sources are easily (if not always instantly or freely) accessible and provide data on key issues including coral bleaching, fisheries, forest cover, greenhouse gas emissions, Key Biodiversity Areas, protected areas, species distribution and abundance, wetlands extent and wildlife trade. However, for the full data landscape to become more manageable and accessible to people who need it most, and to provide all the types of information required, several actions need to be taken by conservationists, scientists and other end users.

Conclusion

The lack of access to biodiversity data is a major impediment to adaptive management in conservation and natural resource management. Managers need to continue to collect primary data for their projects and programmes to monitor progress but, in many cases, their efforts will be enhanced if they can access and use data on biodiversity pressures, states and responses from global sources. Numerous data sources exist and we have identified a preliminary list of some of the potentially most useful, but many are difficult to find, access or use easily. However, if the conservation, science and business communities could make a greater effort to share and publicise data sources and make existing tools and data freely available for the managers who most need them, we might be able to mainstream biodiversity data into decision-making and ultimately stop biodiversity loss.

Supporting information

Acknowledgments

The development of the database inventory was a collaboration between the IUCN SSC Species Monitoring Specialist Group and Global Wildlife Conservation.