Biodiversity management

Climate change has caused local species loss and increased mass mortality for plants and animals, resulting in climate-driven extinctions and declines in the key benefits provided by nature, from clean air and water to raw materials for goods. Monitoring biodiversity is critical for effective conservation management, as well as effective climate mitigation and adaptation action. This is not restricted to the terrestrial environment but also affects marine and freshwater ecosystems. Biodiversity helps to buffer against the impacts of climate change – such as floods, droughts and food insecurity. The ambitious targets of the 30 x 30 landmark agreement reached by the UN Convention on Biological Diversity in December 2022 to protect at least 30 percent of land and sea for nature by 2030, have brought the critical focus on biodiversity management into even sharper focus.

At present, effective biodiversity management is hindered by large gaps in data about biodiversity – from the distribution of species, to their ecological interactions and the effectiveness of different management measures. The data gap is made more challenging by the scale and complexity of the task. Identifying and classifying species accurately can be difficult – and some species remain poorly known (particularly in less studied parts of the world). Alongside this, biodiversity data is needed both at fine-grained local scales and at the global scale – and over longer periods of time. Yet the resources to carry out this level of monitoring evades most scientific researchers or governments. The lack of data can play into a lack of political will by decision makers, making it easier to prioritize short-term economic opportunities above biodiversity targets and undermining aspirations for evidence-based decision making.

Collective intelligence initiatives are increasingly helping to address these data gaps by mobilizing community members, Indigenous populations and volunteers to collect and analyze species data using citizen science and crowdsourcing. In some examples, citizen-generated data on species biodiversity is paired with other sources of data, such as satellite data to help adjust or build globally relevant scientific models. As well as helping to create scientific knowledge, collective intelligence projects that involve members of the public also close the distance gap – helping communities to build awareness and knowledge of their surrounding environment and how it is being changed due to climate pressures. For this reason, many citizen science biodiversity monitoring projects include an explicit educational objective built into their design.   

Main collective intelligence methods being used

  • Participatory sensing for biodiversity monitoring in hard-to-reach locations

  • Citizen science to scale and fast track biodiversity data collection

  • Crowdsourcing Indigenous Knowledge to identify rare biodiversity events

Main climate action gaps being addressed

  • Data gaps about species distribution, ecological interactions and effectiveness of management measures

Participatory sensing for biodiversity monitoring in hard-to-reach locations

Improving knowledge about species distribution in hard-to-reach locations like rainforests and oceans is a pivotal benefit of collective intelligence biodiversity projects. A key method being used in this type of project is participatory sensing which involves groups of people using and collecting information from digital sensors and recording physical changes or conditions in the environment. Sensors can increasingly provide cheap, real-time measures of a wide range of different biodiversity data.

An example of this is Rainforest Connection’s Arbimon platform which has been used in Puerto Rico to conduct island-wide surveys using passive acoustic monitoring (PAM) with in-situ sensors. The acoustic sensors are created using old mobile phones crowdsourced from volunteers, who are also involved in generating biodiversity monitoring data. The platform uses machine learning to identify matching samples and to compare biodiversity monitoring in different locations. These tools have been applied to collect data from 841 sites across the archipelago during the three-month peak of bird breeding season. The large sampling area and the volume of data would be impossible for researchers to gather on their own. The data is used to implement eco-acoustic and conservation monitoring systems including for anti-logging and anti-poaching initiatives, and to drive conservation action by wildlife managers on the ground.

The Secchi app is a citizen science project that estimates phytoplankton biomass from data about ocean transparency. Phytoplankton are microscopic marine algae that underpin the marine food chain and climate change has driven species decline. Researchers’ ability to collect data and understand this effect has lessened over recent years due to the scale and challenging conditions of the ocean which can make it hard to take in-situ measurements. The global Secchi Disk study engages seafarers to fill this data gap using low-cost DIY sensors called Secchi Disks. Seafarers lower the sensor into the water (following a standardized data collection protocol) to obtain readings about water transparency. The aggregated data from the readings can be downloaded by scientists from the project website, where the data is also visualized on a map. In addition to raising awareness about marine ecology to bridge a distance gap, this project is helping to fill a vital data gap for researchers working on marine ecology.

Citizen science to scale and fast track biodiversity data collection

Global environmental monitoring projects are helping to fast track data collection on key biodiversity indicators, creating observation datasets at a scale previously unimaginable for ecologists. Citizen science is already a well-established collective intelligence method for biodiversity data collection in the Global North, but its use is expanding in Global South contexts. It has huge potential to fill data gaps more quickly, cheaply and at much greater scale than can be achieved by scientists working alone. Citizen science initiatives often standardize protocols for data collection and measurement, and use simple tools to enable volunteers to easily contribute to effective environmental monitoring.

For example, through Seagrass-Watch, the global seagrass observation program, citizen scientists have conducted over 5,700 assessments at 418 sites across 26 countries since 1998. The programme has a strong emphasis on consistent data collection, recording and reporting. Seagrass-Watch identifies areas important for seagrass species diversity and conservation, and the information collected is used to assist the management of coastal environments to prevent significant species loss. The hands-on and participatory nature of Seagrass-Watch is at once a cost-effective method of collecting data and helps to build local interest and ownership in management of coastal seagrasses, bridging a key distance gap. The project has generated local support for marine conservation and built closer relationships and partnership networks between community groups and local government for efficient seagrass conservation and management.

The GLOBE observer programme, NASA's largest and longest-lasting citizen science program about Earth, crowdsources observations of Land Cover and Trees with planned expansion to other types of data in the future. Crowdsourcing citizens’ tree observations and measurements of tree height (and optionally tree circumference) with GLOBE Trees, allows for the tracking of tree growth over time. Tree height is the most widely used indicator of an environment's ability to grow trees, and can inform understanding of the gain or loss of biomass. NASA regularly organizes global data collection challenges through the GLOBE programme – these are short, focused periods of data collection that help to generate a lot of data quickly. In 2022, their month-long Trees Challenge helped to generate a dataset of more than 4,700 observations in over 1,500 locations worldwide. This citizen-generated data is used to ground truth satellite observations and contributes to the development of more accurate scientific models of tree coverage, carbon emissions and carbon sequestration.

Crowdsourcing Indigenous knowledge to identify rare biodiversity events

Indigenous communities build up specialized knowledge about local biodiversity over generations, making them well placed to identify unusual or rare signals of climate-related changes to local ecology. However, Indigenous or local knowledge has typically been underrepresented in scientific research and IPCC reports. But it is increasingly acknowledged that the inclusion of Indigenous populations in biodiversity management will enhance the local relevance, appropriateness and sustainability of these interventions. Although significant challenges exist, there are examples of collective intelligence projects that have worked effectively with Indigenous groups to help address the biodiversity data gap and the diversity gap in climate action. In particular, collective intelligence initiatives that work with Indigenous communities tend to make use of their historic and longitudinal knowledge of their local environment to generate data on new or rare events. CyberTracker Kalahari is a platform that scales this expertise and replicates biodiversity field projects in the Kalahari Desert in Southern Africa. The project employs Indigenous trackers to contribute to large-scale, long-term monitoring of biodiversity, ecosystems and landscapes for conservation management using a simple app. The CyberTracker software, which is free, is contributing to environmental conservation worldwide, not just by trackers, but for scientific research, conservation management and anti-poaching – it has been downloaded more than 500,000 times. Similarly, the Local Environmental Observer (LEO) network of local Indigenous observers crowdsources examples of unusual animal, environment and weather events in the Arctic.