Agricultural expansion, driven by the increasing demand on crops, poses a severe threat to the global environment and to human welfare. Regarded as an effective landscape pattern for balancing biodiversity and food security, land sparing bears high expectations from ecologists. To reflect the spatial-temporal pattern change of land sparing, we calculate a land sparing/sharing (LSS) index on the basis of a remote sensing dataset. The land-sparing pattern has shown an apparent increasing trend globally, especially in hotspots, including the eastern United States, central South America, northern Europe, Kazakhstan, southeastern China, and the Korean Peninsula. Meanwhile, the land-sharing pattern has been increasing in some other regions, including in the southeast of South America, western Europe, central Europe, southern Europe, and northwestern China. However, according to statistical datasets, contrary to the overall increasing trend of land sparing, passive land sparing, incentivized by lower food prices due to increased yields, is decreasing, especially in countries with high levels of development. Our results reveal the global trends in land sparing and passive land sparing, providing support for balancing biodiversity conservation and food security among countries and ecoregions.

Biodiversity conservation is the cornerstone for sustainable development. Bold conservation targets provide the last opportunities to halt the human-driven mass extinction. Recently, bold conservation targets have been proposed to protect 30% or 50% of Earth. However, little is known about its potential impacts on cropland. We identify potential cropland losses when 30% and 50% of global terrestrial area is given back to nature by 2030/2050, at three spatial scales (global, biome and country) and using two approaches (“nature-only landscapes” and “shared landscapes”). We find that different targets, applied scales and approaches will lead to different cropland losses: (1) At the global scale, it is possible to protect 50% of the Earth while having minimum cropland losses. (2) At biome scale, 0.64% and 8.54% cropland will be lost globally in 2030 and 2050 under the nature-only approach while by contrast, the shared approach substantially reduces the number of countries confronted by cropland losses, demanding only 0% and 2.59% of global cropland losses in 2030 and 2050. (3) At the national scale, the nature-only approach causes losses of 3.58% and 10.73% of global cropland in 2030 and 2050, while the shared approach requires 0.77% and 7.55% cropland in 2030 and 2050. Our results indicate that bold conservation targets could be considered, especially when adopting the shared approach, and we suggest adopting ambitious targets (protecting at least 30% by 2030) at the UN Biodiversity Conference (COP 15) to ensure a sustainable future for Earth.

Growing demands for food, energy, minerals and other natural resources are intensifying pressure on ecosystems. Meeting these demands while reducing biodiversity loss requires making decisions about which areas can simultaneously support sustainable development, conserve biodiversity and maintain or restore ecosystem services. Existing spatial optimization tools in planning contexts offer limited support to accommodate multiple objectives, such as maximizing agricultural production and biodiversity outcomes, because they rely on predefined formulations that lack the flexibility to incorporate objectives from multiple sectors and explicitly characterize trade‐offs and synergies among them. Here, we present a multi‐objective optimization framework for spatial planning. The framework is used to express multiple planning goals and requirements as optimization problems, identify solutions that simultaneously satisfy multiple objectives and explore trade‐offs between them. It provides a flexible structure for specifying objectives within and across sectors and supports multiple multi‐objective optimization approaches—weighted‐sum, hierarchical and reference point approaches. To promote accessibility, we implemented the framework as an update to the prioritizr R package. Using a multiple‐use case study in the European Union, we demonstrate how the framework supports the identification of solutions that balance trade‐offs between ecosystem restoration, agriculture and forestry production. Synthesis and applications. Our framework enables conservation scientists, planners and practitioners to identify spatial plans that achieve multiple objectives. It is designed to help explore trade‐offs across a broad range of domains, including terrestrial, marine and freshwater realms. By reducing technical barriers, the framework facilitates exploration of trade‐offs and identification of co‐benefits across diverse ecological, economic and social planning contexts.