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The rapidly growing business of solar grazing
Solar grazing offers developers a cost-effective solution to land stewardship and vegetation management, with many other tangible benefits as a bonus.
Scientists Unlock 700,000-Year-Old Secrets Hidden Inside a Giant Elephant Tooth
A giant elephant’s tooth has preserved clues to the watery world that sustained early humans nearly 700,000 years ago. Researchers studying elephant remains from Gesher Benot Ya’aqov (GBY-NBA) in northern Israel have reconstructed a Pleistocene environment rich in water, vegetation, and wildlife. Published in Quaternary Science Reviews, the study reveals the landscape shared by enormous
A 100-kg green anaconda can almost vanish in the Amazon; scientists found giant snakes hiding under logs, leaf matter, vegetation, and riverbanks
Green anacondas can remain difficult to spot in the western Amazon, even when they weigh 100 kg. A study of the snakes in Peru found that they were usually visible only when basking.
The science that brought green back to China’s Loess Plateau awarded the 2026 Volvo Environment Prize
Once stripped of vegetation and scarred by some of the world’s most severe soil erosion, China’s Loess Plateau has undergone a remarkable ecological transformation. Professor Bojie Fu, one of the scientists who helped make that recovery possible, is the recipient of the 2026 Volvo Environment Prize.
In 1971, scientists moved just five pairs of Italian wall lizards onto a small Croatian island; 36 years later their descendants had larger heads, stronger bites and altered digestive tracts suited to eating far more vegetation than the original population
A forgotten experiment in island translocation became an accidental demonstration of evolution in real time, reshaping an entire species in just over three decades.
Viewpoint: Unlocking Europe’s wildfire data
Europe is already investing in the science, technology and infrastructure needed to understand, prevent and fight wildfires. Copernicus provides satellite-based Earth observation and environmental information, while the European Forest Fire Information System provides information on fire danger and forest fires across Europe. Weather and climate systems add forecasts of heat, drought, wind and humidity; historical fire databases show where fires have occurred; and researchers generate increasingly detailed knowledge about fuels, fire behaviour, forecasting, modelling and risk management. Meanwhile, new European research projects are adding digital twins and other tools to this growing ecosystem.However, these data do not necessarily sit together, nor are they necessarily described, structured or governed in ways that allow them to be used together. Much of the information is public, but some is commercially held. Some is sensitive. Some is subject to legal, security or operational restrictions. Even when data can be legally accessed, different systems may use different formats, terminology and rules.Europe therefore faces an unusual paradox: we have vast amounts of relevant information to respond to the wildfire challenge, but not the means to bring it together. For example, a wildfire researcher or emergency service might need to ask whether a particular combination of vegetation, drought, wind and topography has historically been associated with rapid fire spread. The relevant information may exist in several institutions, using different systems and subject to different conditions of access.The challenge is to conduct an authorised analysis that interacts with these sources, combines the results and respects the rules imposed by each data custodian.An important part of the answer can be found in the Fair principles, the idea that data should be findable, accessible, interoperable and reusable. Developed more than a decade ago, these principles have become a central reference point for modern data stewardship, making it easier for people and machines to find data, understand what it means and determine whether it can be reused.Readability by machines is essential, since AI systems will be key to meeting the data challenge. Bring analysis to the dataThe proposition is not to give an AI system unrestricted access to sensitive databases. Quite the opposite. The goal is to make it possible for approved algorithms to go to the data, rather than requiring sensitive data or large datasets to be copied to wherever the analysis happens.Imagine an analysis asking a series of questions of different data stations. At one station it might examine weather and climate data; at another, historical fire records; at another, experimental measurements of fire behaviour. The algorithm does not need to download everything. It can operate within the environment permitted by each data custodian and return only the results that the rules allow to leave.This is sometimes described as data visiting, and related approaches already exist in areas such as federated analysis and federated learning.Sensitive data should therefore not be treated as a free-for-all for machines. This requires appropriate governance at multiple levels. Access needs to be authenticated and authorised. The purpose of an analysis should be defined. The code or model being run should be controlled. Data custodians should be able to specify what can be queried and what results can leave their environment. Activities should be auditable and human oversight should remain where the consequences require it.In other words, the objective is not to trust AI with the data. It is to design systems in which AI never has more access than it needs.As open as possible, as closed as necessaryFair data should also not be confused with open data. Some wildfire data should be openly available. Other information may legitimately need to remain restricted because it concerns critical infrastructure, security, commercial interests, privacy or operational capabilities. The principle should be: as open as possible, as closed as necessary.The important point is that restricted data should not automatically become unusable data. If machines can discover what information exists, understand its meaning, establish where it came from and determine the conditions under which it can be used, authorised analyses can potentially be carried out without the underlying data ever leaving the environment in which it is protected.Restricted data can still be Fair and machine-actionable.This is also an important question of data sovereignty. European institutions should not have to surrender control of their data to a handful of technology platforms in order to benefit from AI. Nor does Europe need to start again by building one giant repository for every piece of wildfire information. The better approach is to connect what already exists.This is the principle behind emerging approaches such as Tryangle, developed through the Leiden Initiative for Fair and Equitable Science. Rather than creating another centralised data warehouse, the approach seeks to provide an interoperable layer through which approved algorithms can visit distributed data sources while respecting the rules of their custodians.In this way, a data station can remain where it is. Its custodians can retain control. Existing databases and applications do not have to be abandoned. What changes is their ability to communicate with other systems through common, machine-readable descriptions, access rules and interoperability mechanisms.But approaches like this need data that meets the Fair principles. Only then can an interoperable ecosystem safely begin to turn fragmented information into collective intelligence.Data infrastructure is wildfire infrastructureThe implications of this approach are entirely practical. Firefighters could gain better intelligence about local and evolving risks. Land managers could test prevention strategies using more comprehensive information about fuels, weather and past fires. Researchers could compare evidence across ecosystems without repeatedly moving huge datasets between institutions. Smaller regions and resource-constrained teams could access analytical capabilities without having to build large data infrastructures themselves.Europe is already investing heavily in satellites, databases, research programmes, forecasting systems and scientific expertise. The question is whether we will connect those investments well enough to turn them into actionable intelligence.That requires policymakers and funders to treat data infrastructure as seriously as physical infrastructure. Data generated or supported through European public funding should be Fair, verifiable and machine actionable by design, wherever legally and ethically possible.Related articlesData Corner: Europe’s burning need for wildfire mitigation researchClimate monitoring must remain a global enterprise, experts sayIn practice, that means funding not only the production of data, but also the infrastructure that makes data usable across systems: metadata, provenance, interoperability, access mechanisms and governance. Where data must remain restricted, we should ensure that it can still be securely discovered, verified and used for authorised analysis.Initiatives such as the European Open Science Cloud offer an existing framework through which these principles can be put into practice. What is needed now is to accelerate implementation and make them a standard part of how Europe funds and builds research and innovation systems.We do not need another generation of disconnected databases. The data is already there. The opportunity is to make it work together, securely, responsibly and quickly enough to help prevent the next fire, rather than simply document the last one.Jean-Claude Burgelman is professor emeritus at the Free University of Brussels (VUB) and editor-in-chief at Frontiers Policy Lab. For more than 20 years he held leading roles in research and innovation policy at the European Commission.
Community Invited to Forest Health and Wildfire Risk Town Hall on Aug. 27
Nevada County community members are invited to attend the “Hard Choices in the Woods: Forests, Fire and Herbicide” Town Hall on forest health and vegetation management tools used to reduce
Community Invited to Participate in the Forest Health and Wildfire Risk Survey
Nevada County community members are invited to attend the “Hard Choices in the Woods: Forests, Fire and Herbicide” informational Town Hall on forest health and vegetation management tools
BLM Approves Projects to Improve Forest Health and Reduce Wildfire Risk in the Fall River Valley
ALTURAS, Calif. – The Bureau of Land Management Applegate Field Office has approved two forest resilience projects in the Fall River Valley, aimed at improving forest health, reducing wildfire risk, and strengthening community preparedness. Work on both projects is expected to begin in fall 2026.
Howard County businesses say BGE needs better vegetation management
HLS Vegetation Indices
In this explainer, each vegetation index includes a visualization, an example application, and a description of the index that highlights how HLS’s increased temporal revisit empowers new research.
Worsening Nebraska drought could impact tree health amid wildfire concerns
As most of western and central Nebraska faces historic drought, the state’s tree experts are concerned drought could proliferate disease and pest concerns. Dry vegetation and trees also compound wildfire risk.
Tracy Arm’s Post-Tsunami Landscape
A landslide-triggered tsunami stripped vegetation from the shore of the glacial fjord in summer 2025.