Understanding Data

This section explores how data is used in conservation—from initial collection methods to the analysis that informs real-world action. Conservation data helps us track species, understand ecosystems, and address environmental threats, ultimately guiding effective strategies to preserve biodiversity.

Why Conservation Data Matters?

Conservation relies on data to guide decision-making, assess ecosystems, and understand the complex relationships between species and their environments. Without reliable data, it’s difficult to prioritise which species or habitats need urgent attention or to track the progress of conservation efforts. Data helps identify patterns of biodiversity loss, habitat degradation, and the impact of human activity. It also allows for evidence-based strategies, ensuring resources are used efficiently and effectively.

Types of Data in Conservation

Conservation data can be grouped into several key categories that, together, provide a full picture of ecosystem health and pressures:

Biological Data: Information on species populations, behaviors, interactions, genetics, and health issues like diseases. These insights are essential for understanding individual species and how they interact within ecosystems.
Environmental Data: Data covering habitat conditions, climate, water quality, and other environmental factors. This data helps us understand how external conditions affect species and ecosystems.
Human Activity Data: Data on land use, pollution, and community interactions with nature, offering insights into how human activities impact ecosystems directly and indirectly.
Synthetic Data: By building simulations, scientists can explore scenarios to test how different variables impact conservation efforts. This allows researchers to ask “what if” questions and predict outcomes under various conditions.

How We Collect Conservation Data

Data collection methods in conservation vary widely, from field observations to cutting-edge remote sensing and crowd-sourced citizen science contributions. These techniques provide a wealth of information on biodiversity, ecosystems, and environmental changes.

Field Research

Field research involves direct interaction with natural habitats, allowing scientists to observe species and ecosystems firsthand. Common methods include:

Observational Studies: Tracking species populations, habitat use, and reproductive rates by going into the field and monitoring what is seen, with minimal interaction.
Biological Sample Collection: Gathering samples such as blood or other tissue to monitor disease or genetic diversity.
Environmental DNA (eDNA): By analyzing DNA found in environmental samples (like water, soil, snow, or air), scientists can detect which species are present in an area without direct observation. These samples contain DNA from species that have interacted with these materials.
Historical Collections: Studying preserved specimens collected from the field in the past to identify changes in species traits, such as coloration or size over time or between species.

Remote Sensing

Remote sensing technologies allow conservationists to gather large-scale data with minimal or no direct contact with the environment. These tools are invaluable for monitoring remote or difficult-to-access regions:

Camera Traps: Motion-activated cameras strategically placed to capture wildlife activity, offering insights into animal behaviors and population dynamics, particularly useful for elusive or nocturnal species.
Acoustic Surveys: Using microphones to identify species based on their vocalizations. These can be left in place to record continuously, especially useful for tracking birds or marine mammals.
Drones: Robots that allow for close-up data collection in dangerous or inaccessible areas. Drones can collect various data types, such as photos, acoustics, or environmental samples.
Satellite Imagery: Used to monitor land changes like deforestation and habitat fragmentation over time, offering a big-picture view of environmental shifts.
Weather Stations: Passive climate and weather data collection, helping to predict environmental changes and understand ecosystem conditions.

Citizen Science Data

Citizen science involves everyday people contributing to data collection. This can range from logging wildlife sightings through apps to participating in organized data collection efforts like bird counts. Citizen science is essential for conservation by generating large datasets that would otherwise be too costly or time-consuming for professional researchers. It also empowers communities to engage directly in conservation efforts.

Simulation Data

Machine learning and simulations are powerful tools for conservation, enabling researchers to build data-based models that predict outcomes and test variables without impacting real-world ecosystems. For instance, machine learning can help identify patterns in animal movement or habitat use, providing insights that guide future conservation decisions.

Interpreting and Using Data

Collecting data is only part of the equation; the next step is making sense of it through visualisation, trend analysis, and metrics that measure conservation success.

Data Visualisation

Data becomes much more accessible and meaningful when it’s visualised through maps, graphs, and infographics. These tools help scientists, policymakers, and the public quickly understand complex datasets and see patterns at a glance. For example, maps that highlight regions of high biodiversity loss can inform conservation priorities.

Analysing Trends

Trend analysis involves examining data to identify patterns, such as species population changes or habitat degradation over time. By studying trends, conservationists can:

Detect early signs of issues (e.g., species decline)
Evaluate the effectiveness of conservation actions
Adjust strategies to better protect ecosystems

Trend analysis plays a crucial role in shaping policy and conservation priorities.

Success Metrics in Conservation

To assess the impact of conservation efforts, scientists use specific metrics, including:

Population Recovery Rates: Tracking species population numbers to measure growth rates as an indicator of conservation success.
Habitat Restoration: Measuring the extent of ecosystems restored or protected.
Species Protection Levels: Assessing legal protections and other conservation actions that directly benefit species.

These metrics not only validate conservation efforts but also provide critical feedback for ongoing improvement. Effective conservation is an iterative process—each step is informed by data, analysis, and careful monitoring to ensure that species and ecosystems continue to thrive.

Figure 1: Bar graph showing the species diversity of insects in the UK at different taxonomic levels (toggle with +/-). The bar graph was made on tableau public, and the data is obtained from NBN Atlas (NBN Trust ([2024]). The National Biodiversity Network (NBN) Atlas. https://ror.org/00mcxye41.)

Here are some general conservation resources:

Relevant resources for this topic will be added soon. Check back later for useful links, articles, and tools to support conservation efforts.