Forest Biodiversity Monitoring with Stora Enso

Biodiversity monitoring
Digitalization
Innovative data collection
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Industry

Renewable materials

Revenue

2021

€10.2B

Employees

2021

22,000

Countries

2021

50+

About

Forests are the foundation for Stora Enso's renewable offerings. We aim to produce renewable resources, enhance biodiversity, and help combat global warming – all while maintaining forest health. Now we are looking for digital solutions to remotely monitor and measure forest biodiversity in line with our ambitious 2030-2050 sustainability targets.

Opportunity overview

Biodiversity is profoundly vital for the planet and humankind. At Stora Enso, biodiversity management is an integral part of our forest management practices. In 2021, Stora Enso announced their new sustainability ambition to safeguard and enhance biodiversity to achieve a net-positive impact on biodiversity in our own forests and plantations by 2050. A set of actions towards 2030 has been developed and initiated to improve biodiversity on species, habitat and landscape levels.

For reaching our sustainability targets, we are looking for solutions that can digitally and remotely monitor biodiversity and the impact of our actions at scale. Today, biodiversity monitoring is conducted via sustainability field agents with a combination of manual and digital collection. We are looking for a digital solution that can remotely collect and analyse science based data streams for forest, species and habitat levels at scale (1000’s to 10’000’s of hectares per day).

Ideal solution would be accurate science-based data monitoring capable of collecting digital data streams in line with Stora Enso biodiversity indicators (read more here). Potential solution could be a pure software solution or a combination with hardware. We are also interested in solutions that enable determining the age of the forest through remote sensing, computer vision, AI or image recognition solutions based on the available data.

Your opportunity with Stora Enso

Today, Stora Enso is one of the largest private forest owners in the world with total forest assets valued at more than EUR 8 billion in 2021. We are looking for innovative solution providers who are keen on to enhance biodiversity and help combat global warming together with us. We are ultimately looking for a long-term technology partner to supply current and future digital monitoring (2023-2050), and to support us to reach our sustainability goals. We would like to work together and share our industry knowledge to provide you valuable information enabling your company further opportunities within the industry.

Examples of focus areas we want to measure, initially:

Soil and water preservation

The driving of harvesting machines in the forest requires careful planning to avoid damaging the soil and water. Measured as percentage of affected streams, lakes or wetlands.

Tree retention

Trees that are left on site after harvesting are called retention trees. The trees can support biodiversity over the forest regeneration phase. Measured as percentage of volume left in the area.

Dead wood preservation

Many species in boreal forests depend on deadwood. Monitoring how much deadwood is left at harvesting sites and whether damage to deadwood is avoided. Measured as percentage of affected logs.

High stumps

High stumps increase the amount of deadwood and thereby contribute to restoring more natural forest-like conditions in managed landscapes. Measured as number of stumps in a hectare.

Preserving prioritized habitats

The natural variation of the forest is considered in harvesting operations, and precautions are taken to preserve prioritised habitats properly. Measured as percentage of affected habitat/zones.

Determining tree age

Accurate determination of the forest age is crucial in forest management, to be able to save the stands with high nature conservation value and align with legislation. Today, the age of a stand is done by estimation: one tree is drilled and its rings are counted through the hole. The ideal solution would be digital, accurate and remote. It would determine the age using different sources of existing data including old orthophotos and increment graphs.

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