Optimising nature conservation outcomes for a given region‐wide level of food production

Risk-appropriate regulations for gene-editing technologies

This paper explores the scope for the newly emerging technologies, based on gene editing (GE) contributing to addressing the global challenges that we face. These challenges relate to food security, climate change and biodiversity depletion. In particular, it examines the science and evidence behind the most appropriate forms of agricultural production to meet these challenges, the targets set in the Global Biodiversity Framework (GBF) agreed to at the end of 2022 and the possible role of GE technologies in contributing to meeting these targets. It then examines the most risk-appropriate regulatory environment required to best facilitate the adoption of GE technology, drawing on the experiences of the impact of regulatory systems for other innovations used in agricultural and food production systems such as genetically modified organisms (GMOs).

Land sharing complements land sparing in the conservation of disturbance-dependent species

Alteration of natural disturbances in human-modified landscapes has resulted in many disturbance-dependent species becoming rare. Conservation of such species requires efforts to maintain or recreate disturbance regimes. We compared benefits of confining efforts to habitats in protected areas (a form of land sparing) versus integrating them with general management of production land (a form of land sharing), using two examples: fire in forests and grazing in semi-natural grasslands. We reviewed empirical studies from the temperate northern hemisphere assessing effects of disturbances in protected and non-protected areas, and compiled information from organisations governing and implementing disturbances in Sweden. We found advantages with protection of areas related to temporal continuity and quality of disturbances, but the spatial extent of disturbances is higher on production land. This suggests that an approach where land sparing is complemented with land sharing will be most effective for preservation of disturbance-dependent species in forests and semi-natural grasslands.

Habitat percolation transition undermines sustainability in social-ecological agricultural systems

Steady increases in human population size and resource consumption are driving rampant agricultural expansion and intensification. Habitat loss caused by agriculture puts the integrity of ecosystems at risk and threatens the persistence of human societies that rely on ecosystem services. We develop a spatially explicit model describing the coupled dynamics of an agricultural landscape and human population size to assess the effect of different land-use management strategies, defined by agricultural clustering and intensification, on the sustainability of the social-ecological system. We show how agricultural expansion can cause natural habitats to undergo a percolation transition leading to abrupt habitat fragmentation that feedbacks on human's decision making, aggravating landscape degradation. We found that agricultural intensification to spare land from conversion is a successful strategy only in highly natural landscapes, and that clustering agricultural land is the most effective measure to preserve large connected natural fragments, prevent severe fragmentation and thus, enhance sustainability.

Consequences of underexplored variation in biodiversity indices used for land-use prioritization

For biodiversity protection to play a persuasive role in land-use planning, conservationists must be able to offer objective systems for ranking which natural areas to protect or convert. Representing biodiversity in spatially explicit indices is challenging because it entails numerous judgments regarding what variables to measure, how to measure them, and how to combine them. Surprisingly few studies have explored this variation. Here, we explore how this variation affects which areas are selected for agricultural conversion by a land-use prioritization model designed to reduce the biodiversity losses associated with agricultural expansion in Zambia. We first explore the similarity between model recommendations generated by three recently published composite indices and a commonly used rarity-weighted species richness metric. We then explore four underlying sources of ecological and methodological variation within these and other approaches, including different terrestrial vertebrate taxonomic groups, different species-richness metrics, different mathematical methods for combining layers, and different spatial resolutions of inputs. The results generated using different biodiversity approaches show very low spatial agreement regarding which areas to convert to agriculture. There is little overlap in areas identified for conversion using previously published indices (mean Jaccard similarity, J_w , between 0.3 and 3.7%), different taxonomic groups (5.0% < mean J_w  < 13.5%), or different measures of species richness (15.6% < mean J_w  < 33.7%). Even with shared conservation goals, different methods for combining layers and different input spatial resolutions still produce meaningful, though smaller, differences among areas selected for conversion (40.9% < mean J_w  < 67.5%). The choice of taxonomic group had the largest effect on conservation priorities, followed by the choice of species richness metric, the choice of combination method, and finally the choice of spatial resolution. These disagreements highlight the challenge of objectively representing biodiversity in land-use planning tools, and present a credibility challenge for conservation scientists seeking to inform policy making. Our results suggest an urgent need for a more consistent and transparent framework for designing the biodiversity indices used in land-use planning, which we propose here.