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Exploring data: Pollinator Count
Data from Pollinator counts done at the Natural History Museum and RHS gardens in 2024 and 2025.
Learners can start working with data to answer questions and practise key skills in science, math, and critical thinking. Learners can also use this as a starting point for planning where and how they might want to conduct their own pollinator counts.
Preparation
What you need
- Downloaded pollinator count data
- Graphing software or pen and paper
Location
Indoors
About the data
The RHS pollinator count data was gathered by staff or trained volunteers. They carried out the UK Pollinator Monitoring Scheme's FIT count (Flower-Insect Timed count) survey. The Nature Park Pollinator Count is based on this more detailed survey. The FIT count data was simplified to match the format of the Nature Park Pollinator Count. The spreadsheet has second tab with more condensed data which aligns with the focused survey, where participants sort insects into five easily recognised groups.
The NHM Pollinator count data was collected by families visiting the Natural History Museum in London. They only did the focused pollinator count. NHM staff picked the survey spots, making sure they included plants likely to attract pollinators.
Starting suggestions
Graph the number of insects observed in different weather conditions. Are all insect groups impacted by weather in the same way?
Graph the number of insects observed on different plant species. Do bumblebees have a favourite species to visit?
Reflection
What questions can’t be addressed by these datasets?
Questions related to how insect populations are changing over time are not well addressed by this data. Insects are sensitive to weather conditions such as temperature or rainfall. A short spell of the wrong weather conditions can kill a large number of insects in an area. However, many insects reproduce very quickly. This means if their numbers drop one year, they can often bounce back the next. This short-term variability can hide long-term patterns caused by changes to land use or climate change. Data from many years is needed to see these long-term trends.
What data can you collect and add to these datasets that would help answer questions you might have?
Curriculum links
Mathematics - Statistics
- complete, read and interpret information in tables, including timetables
- decide which representations of data are most appropriate and why
Science - Working scientifically
- recording data and results of increasing complexity using scientific diagrams and labels, classification keys, tables, scatter graphs, bar and line graphs
Mathematics - Statistics
- construct and interpret appropriate tables, charts, and diagrams, including frequency tables, bar charts, pie charts, and pictograms for categorical data, and vertical line (or bar) charts for ungrouped and grouped numerical data
- describe simple mathematical relationships between 2 variables (bivariate data) in observational and experimental contexts and illustrate using scatter graphs
Science - Working scientifically
- apply mathematical concepts and calculate results
- present observations and data using appropriate methods, including tables and graphs
- interpret observations and data, including identifying patterns and using observations, measurements and data to draw conclusions
Science - Working scientifically
- applying the cycle of collecting, presenting and analysing data
- presenting observations and other data using appropriate methods
- translating data from one form to another
- interpreting observations and other data, including identifying patterns and trends, making inferences and drawing conclusions
What to try next
Add flower-rich grassland
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