The study, published in Nature Food, follows environmental impacts through global agricultural supply chains rather than examining land-use change in isolation. This approach makes it possible to connect a particular food product with the landscapes used to produce it and with the consumers whose demand ultimately drives production. The researchers assessed how converting or intensifying land for agriculture affects long-term carbon storage and biodiversity, then tracked those impacts across international trade and consumption networks.

The geographic pattern is striking. The Northern Hemisphere experiences greater carbon loss overall, while the Southern Hemisphere suffers higher biodiversity loss. Yet these two environmental pressures are not separated neatly by latitude. Areas with high carbon losses and areas with high biodiversity losses are often located in the same regions, meaning that protecting one environmental service could frequently help protect the other. The overlap also shows that food production is not creating evenly distributed damage: approximately two-thirds of total losses occur within just one-third of the total area examined.

This concentration is scientifically and politically important. Carbon storage is a major component of the climate system because vegetation and soils can retain carbon for long periods, preventing it from accumulating in the atmosphere. Biodiversity, meanwhile, reflects the variety of species, habitats and ecological functions that sustain resilient ecosystems. When natural land is converted for crops or pasture, both carbon-rich ecosystems and biological communities can be disrupted. The new mapping shows that these impacts can be traced to specific production zones instead of being treated as diffuse, global consequences.

The analysis also identifies food consumption as the dominant force behind the losses. Consumption is responsible for 83% of the carbon and biodiversity losses measured in the study. Animal-sourced foods alone account for 59% of carbon losses and 71% of biodiversity losses. This difference suggests that animal agriculture has a particularly strong connection to biodiversity damage, even though its contribution to carbon loss is also substantial. The results point to the importance of examining not only how food is produced, but also what foods are demanded and where that demand originates.

Bovine meat and milk stand out as the largest product-level contributors. Together, they account for 29% of carbon losses and 41% of biodiversity losses linked to the food system. Cattle production can require extensive land for grazing and feed, so its environmental footprint may extend far beyond the fields or pastures where animals are raised. A supply-chain perspective captures these indirect effects, revealing how consumer choices can influence land-use pressures thousands of kilometres away.

International trade further separates the locations of environmental damage from the locations of consumption. Brazil emerges as the world’s largest net exporter of both carbon and biodiversity losses, meaning that its agricultural production supplies overseas demand while transferring a large share of associated environmental impacts beyond its borders. China is identified as the largest net importer for both categories. In both countries, animal products dominate the relevant flows, illustrating how global trade can connect livestock production landscapes with distant markets and consumers.

The researchers’ high-resolution approach could help governments move beyond broad national averages. A country may appear to be reducing its domestic environmental pressure while importing products associated with land-use change elsewhere. Conversely, a producing region may bear the ecological costs of supplying food consumed abroad. By tracing impacts through products and trade, the study provides a way to identify where interventions could produce the greatest benefits. These interventions could include changes in consumer demand, improved production practices, stronger land-use protections and supply-chain policies targeting high-impact commodities.

The findings do not suggest that a single measure will solve the food system’s environmental footprint. Instead, they highlight the need for coordinated action focused on the regions and products responsible for the largest combined losses. Reducing pressure from high-impact animal products, protecting carbon-rich and biodiverse landscapes, and improving transparency in international supply chains could help align climate and conservation goals. Because the greatest losses are concentrated geographically and strongly linked to a limited group of foods, the study indicates that carefully targeted policies may deliver larger gains than unfocused global efforts. The message is clear: what appears on the plate can determine the fate of forests, soils, species and stored carbon far beyond the consumer’s immediate surroundings.

Subject of Research: Global carbon storage and biodiversity loss caused by land use in agricultural supply chains.

Article Title: High-resolution carbon and biodiversity mapping shows correlated losses across space and agricultural products.

Article References: Liu, B., Behrens, P., Sun, Z. et al. High-resolution carbon and biodiversity mapping shows correlated losses across space and agricultural products. Nature Food (2026). https://doi.org/10.1038/s43016-026-01387-0

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s43016-026-01387-0

Keywords: carbon storage, biodiversity loss, agricultural supply chains, food systems, land use, animal-sourced foods, bovine meat, milk, global trade, climate policy, conservation, Brazil, China

A new study published in Nature addresses a major obstacle to climate-aware restoration policy: the absence of a continent-wide, high-resolution picture of where wetlands are, what types they are, and how disturbed they have become. Led by researchers at the Global Wetland Center at the University of Copenhagen, the work aims to make wetland restoration targets measurable and actionable across Europe.

“To meet wetland restoration targets, we need a high-resolution map showing their extent, the different types, and what is disturbing them today,” says lead author Gyula Máté Kovács. He emphasizes that without such insight, it is difficult to assess wetlands’ true climate impact—especially where restoration potential is greatest.

Using 10-meter satellite imagery and machine learning, the team produced an open-access digital product called European Wetland Types. The map classifies six categories of natural and semi-natural wetlands across 38 European countries, enabling consistent, cross-border comparisons of wetland extent and condition.

The researchers highlight that Europe’s wetlands are highly fragmented. Roughly 27–33% occur in contiguous areas smaller than 25 hectares, and 7–11% are found in patches under 1 hectare. Because many existing datasets are too coarse, the smallest wetlands may be systematically missed—reducing the accuracy of restoration planning and carbon risk assessments.

Across the mapped region, about one fifth of wetlands are highly affected by human activity. Inland marshes emerge as among the most disturbed, while peatlands are flagged as a top priority for climate benefits due to their strong capacity to store soil carbon.

However, the stakes extend beyond biodiversity. The study estimates that up to five billion tonnes of CO₂-equivalent soil carbon may have been released compared with a scenario where these wetlands remained undisturbed—an amount comparable to roughly 1.5 years of total EU CO₂ emissions.

Built to support implementation of the EU Nature Restoration Law, the map helps member states identify restoration candidates and estimate likely climate outcomes. By harmonizing how wetlands are defined across countries, it also allows EU institutions to evaluate reporting on a comparable basis.

The team is now extending the approach to develop a global version of the map, with the goal of improving worldwide estimates of greenhouse gas emissions from wetlands and guiding restoration strategies at larger scales.

Subject of Research: Wetland distribution, fragmentation, condition, and restoration potential across Europe
Article Title: Highly fragmented European wetlands with uneven restoration needs
News Publication Date: 15-Jul-2026
Web References: https://doi.org/10.1038/s41586-026-10760-9 ; https://ee-gmkovacs.projects.earthengine.app/view/european-wetland-types
References: Nature (2026), study DOI: 10.1038/s41586-026-10760-9
Image Credits: Not provided

Keywords

Wetlands, peatlands, satellite mapping, machine learning, carbon sinks, greenhouse gas emissions, EU Nature Restoration Law, biodiversity restoration, habitat fragmentation, 10m resolution

At its core, LiDAR technology functions by emitting laser pulses and measuring the time it takes for reflected light to return—a process that enables accurate distance measurement and 3D spatial reconstruction. Traditional LiDAR systems primarily rely on fixed optical elements that are optimized for a single mode of operation, limiting their flexibility. The team’s approach changes this paradigm by integrating hybrid cascaded metasurfaces that can be mechanically tuned to adapt the light-matter interactions dynamically. These metasurfaces, consisting of precisely engineered nanostructured layers, can manipulate the phase, amplitude, and polarization of incident light with outstanding control. Such manipulation is pivotal for tailoring the emitted laser beams’ characteristics, therefore enabling the system to toggle between dual operational modes optimally.

The significance of a dual-mode LiDAR lies in its capacity to cater to diverse sensing requirements without the need for multiple dedicated systems. The researchers designed the system to switch between a wide field-of-view mode suitable for rapid environmental scanning and a high-resolution mode dedicated to detailed object profiling. This duality means that an autonomous vehicle, for example, can rapidly gather an overall situational map and then focus in on specific objects or hazards with heightened scrutiny, improving both efficiency and safety. Achieving this in a compact and lightweight setup addresses long-standing challenges in the field, where bulky and rigid optics have limited LiDAR implementations.

Mechanically tunable hybrid cascaded metasurfaces enable this transformative switching ability by stacking multiple nanostructured metasurface layers with complementary optical functions. The mechanical tuning involves minuscule adjustments in the relative positioning or orientation of these layers, effectively modulating the resulting optical output. This approach circumvents the limitations seen in traditional electronic modulation of metasurfaces, which often suffer from slow response times or limited tuning ranges. Through precise mechanical actuation, the team realized fast and reversible shifts in beam-shaping capabilities, switching between the wide-angle and focused laser emission modes fluidly. The hybrid nature of these metasurfaces leverages the strengths of different nanostructured elements, synergizing to produce effects unattainable by a single metasurface design.

From a fabrication standpoint, constructing these cascaded metasurfaces involves high-resolution lithography techniques that pattern subwavelength features with nanometer precision. Coupling these surfaces mechanically without incurring optical losses or alignment drifts is a formidable engineering challenge that the research team successfully addressed. The resulting system exhibits high optical efficiency and robustness, important metrics for real-world deployments where environmental conditions can be harsh. Additionally, the mechanical tunability mechanism has been miniaturized to integrate seamlessly with the metasurface stack, preserving a compact footprint tailored for mobility applications.

The experimental results demonstrate that the newly developed LiDAR system achieves rapid switching between its two operational modes in milliseconds, a timescale conducive to real-time sensing scenarios. In its wide field-of-view mode, the emission angle expands significantly, enabling comprehensive spatial awareness albeit with modest resolution. Conversely, the focused mode generates narrow laser beams with increased intensity, facilitating the capture of detailed features such as object shapes and surface textures. Importantly, the system maintains high signal fidelity across both operational states, indicating that the mechanical tuning does not compromise the laser beam quality or detection sensitivity.

Beyond the immediate engineering advances, the dual-mode LiDAR represents an important conceptual advance in reconfigurable photonic devices. By demonstrating practical mechanical tunability in cascaded metasurface assemblies, this work opens the door to smart optical systems that can adapt their functions in real time. Such adaptability is particularly valuable for autonomous systems navigating complex, dynamic environments where sensing requirements vary continuously. The technology could fundamentally reshape approaches not only in LiDAR but also in related fields such as augmented reality, optical communications, and environmental monitoring.

The researchers emphasize the potential applications in autonomous vehicles, where situational awareness is critical to safety. The integration of this dual-mode LiDAR could allow vehicles to balance the need for rapid global perception with targeted, high-resolution inspection of obstacles or pedestrians. Moreover, the compact nature of the metasurface-based system lends itself well to deployment on drones and robots, where payload constraints typically limit sensor capabilities. The adaptability embedded in the metasurface design offers a streamlined way to enhance the functional versatility of these platforms without adding bulk or power consumption.

Crucially, the advances in mechanical tunability demonstrated here solve persistent trade-offs related to beam steering and focusing in conventional LiDAR systems. Existing beam steering usually involves bulky mechanical parts or slow electronic phased arrays, either of which restrict responsiveness or increase complexity. In contrast, the hybrid cascaded metasurface approach harnesses nanofabrication gains with precise mechanical adjustments to deliver an agile, compact alternative. This shift could spark a new wave of innovation in photonic device engineering, where reconfigurable metasurfaces provide adaptive optical front-ends for a variety of sensors and imaging systems.

Furthermore, the materials chosen for the metasurface constructs exhibit high optical damage thresholds and environmental stability, ensuring long service lifetimes under diverse operating conditions. This robustness is critical for commercial viability, particularly in outdoor or industrial contexts where dust, temperature fluctuations, and vibrations pose challenges. The research team also investigated the scalability of their fabrication process, indicating that mass production is feasible using current semiconductor manufacturing infrastructures. This scalability opens avenues for widespread adoption of mechanically tunable metasurface-enabled LiDARs across the mobility and robotics sectors.

Looking ahead, Zhang and colleagues outline opportunities for extending the concept by integrating active control elements such as micro-electro-mechanical systems (MEMS) to further accelerate and automate tuning processes. Combining electrical and mechanical actuation could enhance the system’s flexibility and allow complex tuning sequences that respond dynamically to sensory inputs. Additionally, tailoring the metasurface designs to operate across different wavelength bands promises compatibility with various laser sources and application domains, from ultraviolet imaging to long-range infrared sensing. Such versatility would further consolidate metasurface-based LiDAR as a transformative technology platform.

This pioneering demonstration of a dual-mode LiDAR system epitomizes the potential unlocked by the intersection of nanophotonics and mechanical engineering. By forging mechanically tunable hybrid cascaded metasurfaces, the researchers have delivered a novel pathway toward versatile, high-performance LiDAR that adapts in real time to diverse sensing challenges. As autonomous and intelligent systems become increasingly ubiquitous, innovations like this will underpin the next generation of environmental perception technologies. The convergence of adaptive optics and dynamic mechanical control heralds a new era in which sensors are not just passive observers but intelligent partners in navigation and decision-making.

In summary, the confluence of metasurface engineering, mechanical tuning, and LiDAR technology in this work offers a paradigm shift from fixed-function to multifunctional, reconfigurable sensing platforms. The team’s success not only advances scientific understanding in nanophotonic device design but also paves the way for practical, real-world deployments where adaptability and compactness are paramount. As industries embrace automation and robotics, the importance of flexible sensing modalities like the dual-mode LiDAR system reported here will only grow, catalyzing innovation across transportation, manufacturing, and beyond. The research sets a new benchmark for what can be achieved when nanotechnology is harnessed in concert with innovative mechanical solutions.

Subject of Research: Mechanically tunable hybrid cascaded metasurfaces enabling a dual-mode LiDAR system.

Article Title: A dual-mode LiDAR system enabled by mechanically tunable hybrid cascaded metasurfaces.

Article References:

Zhang, L., Zhang, C., Zhang, L. et al. A dual-mode LiDAR system enabled by mechanically tunable hybrid cascaded metasurfaces.
Light Sci Appl 14, 287 (2025). https://doi.org/10.1038/s41377-025-01999-4

Image Credits: AI Generated

DOI: https://doi.org/10.1038/s41377-025-01999-4