GA_SPM_A4_59;60

Knowledge gaps (in data, indicators, inventories, scenarios):

Data, inventories and monitoring on nature and the drivers of change
• Data on ecosystem processes (including rates of change) that underpin nature’s contributions to people and ecosystem health
• Data from monitoring of ecosystem condition (generally less well represented than ecosystem extent)
• Data on changing interactions among organisms and taxa
• Impacts of increasing CO2 upon the total Net Primary Production of marine systems, and consequences for ecosystem function and nature’s contributions to people
• Syntheses of how human impacts affect organismal traits and global patterns and trends in genetic composition
• Data on extinction risks and population trends, especially for insects, parasites and fungal and microbial species
• Indicators on the global extent and consequences of biotic homogenization, including genetic homogenization
• Global spatial datasets on key threats, e.g., data on patterns in the intensity of unsustainable exploitation of species and ecosystems
• More comprehensive understanding of how human-caused changes to any Essential Biodiversity Variable class (e.g., ecosystem structure) have impacts on others (e.g., community composition) and on nature’s contributions to people
• Data gaps in key inventories: World Database on Protected Areas, the World Database of Key Biodiversity Areas™, red lists of threatened species and ecosystems, and the Global Biodiversity Information Facility
• Monitoring of many listed species in the Convention on International Trade in Endangered Species of Wild Fauna and Flora.
• Monitoring of the long-term effects of dumped waste, especially radioactive material and plastics
• Data on the impacts of war and conflict on nature and nature’s contributions to people

Gaps on biomes and units of analysis
• Inventories on under-studied ecosystems: freshwater, Arctic, marine/ocean, seabed, and wetlands
• Inventories in soil, benthic and freshwater environments, and the implications for ecosystem functions

Taxonomic gaps
• Basic data on many taxa (86 per cent of existing species on Earth and 91 per cent of species in the ocean still await description)
• Extinction risks and population trends for the following taxonomic groups: insects, fungal species, microbial species (microorganisms) and parasites
• Data on the genetic diversity and conservation status of breeds of farmed and domestic plants and animals

NCP-related gaps
• Data on the status of species and nature’s contributions to people linked to specific ecosystem functions
• Systematic indicators to report the status and trends for categories of nature’s contributions to people
• Data on the impacts and extent of nature’s contributions to people on quality of life, by major user group (also lacking an agreed typology on major user groups)
• Data on the interrelationships between gender equality, nature and nature’s contributions to people
• Data and information on NCP 10: regulation of detrimental organisms and biological processes (populations of vectors and vector-borne diseases) and overlaps with vulnerable human populations and ecosystem interactions
• Data and information on NCP 9: the role of nature and nature’s contributions to people in mitigating or reducing vulnerability to disasters

Links between nature, nature’s contributions to people and drivers with respect to targets and goals
• Understanding on how nature contributes to achieving targets (the positive and negative relationships between nature and targets/goals like the Sustainable Development Goals)
• Disaggregated data on the impacts that nature has on good quality of life, particularly across regions, societies, governance systems, and ecosystems
• Need for indicators for some Sustainable Development Goals and Aichi Biodiversity Targets (e.g., Aichi Biodiversity Target 15 on ecosystem resilience and contribution of biodiversity to carbon stocks and Target 18 on integration of traditional knowledge and effective participation of indigenous peoples and local communities)
• Better quantitative data to assess the Sustainable Development Goals and Aichi Targets where qualitative indicators havebeen dominant (9 out of 44 targets under the Sustainable Development Goals reviewed)
• Data on the benefits to human mental health from exposure to natural environments
• Indicators that reflect the heterogeneity of indigenous peoples and local communities

Integrated scenarios and modelling studies
• Regional and global socioeconomic scenarios explicitly considering the knowledge, views and perspectives of indigenous peoples and local communities
• Regional and global ssocioeconomic scenarios developed for, by and in collaboration with indigenous peoples and local communities and their associated institutions
• Quantitative data showing how nature, its contributions to people, and good quality of life interact and change in time along different pathways
• Scenarios of the future of biodiversity which quantify the possible co-benefits related to nature’s contributions to people
• Scenarios about nonmaterial benefits to people compared to material benefits and regulating benefits
• Integrated scenarios for areas projected to experience significant impacts and possible regime shifts (e.g., Arctic, semi-arid regions, and small islands)
• Knowledge about the interaction, feedback and spill-overs among regions within future global scenarios
• Assessment of nature’s contributions to people across scenario archetypes with robust knowledge and quantitative estimates

Potential policy approaches
• Data to analyse the effectiveness of many policy options and interventions, including:
a) Data on the comparative effectiveness of different area-based conservation mechanisms (e.g., protected areas, other effective area-based conservation measures) in conserving nature and nature’s contributions to people and contributing to good quality of life
b) Indicators of the effectiveness of different restoration methodologies and to assess restoration progress over time (including values)
c) Data on the comparative effectiveness of different processes of access and benefit sharing to ensure fairness and equity
d) Better data on the global extent and forms of wildlife trafficking and its impacts on nature and nature’s contributions to people
e) Data on the comparative effectiveness of different models for reconciling bioenergy and biodiversity conservation
f) Data on the effectiveness of different schemes and models for payment for ecosystem services (PES), particularly the trade-offs that arise between policy goals, the integration of multiple values in PES, data on the profiles of PES participants and long-term monitoring of relational and behavioural implications of participation
g) Data on the comparative effectiveness of different models of marine governance relating to conservation
• Data on the extent of the participation of indigenous peoples and local communities in environmental governance
• Indicators on the impacts of environmentally harmful subsidies and trends and effectiveness of their removal at the global level
• Data on areas of uncertainty in applying the precautionary principle
• Data on the monitoring of policy effectiveness to adapt and adjust policies and to share lessons
• Data on the impacts of resource mobilization, using robust program evaluation methods (e.g., examples of successful use of funding including impacts of donor funding for conservation and impacts of specific biodiversity financing projects)
• Data on the impacts of climate change on marine and coastal governance regimes
• Data on the impacts of mainstreaming of biodiversity across sectors
• Better data to develop biodiversity and environmental quality standards

Indigenous Peoples and Local Communities
• Agreed-upon methods to enable systematic processes of knowledge generation, collection and synthesis regarding indigenous and local knowledge (for assessments and elsewhere) and participation of indigenous peoples and local communities in this process
• Syntheses of indigenous and local knowledge about the status and trends in nature
• Data to assess how progress in achieving goals and targets affects indigenous peoples and local communities, either in positive or in negative ways
• Trends in relation to the socioeconomic status of indigenous peoples and local communities (e.g., noting the lack of data differentiation in aggregate statistics)