Ecosystems are under increasing pressure from human activities, with land use and land‐use change at the forefront of the drivers that provoke global and regional biodiversity loss. The first step in addressing the challenge of how to reverse the negative outlook for the coming years starts with measuring environmental loss rates and assigning responsibilities. Pinpointing the global pressures on biodiversity is a task best addressed using holistic models such as Life Cycle Assessment (LCA). LCA is the leading method for calculating cradle‐to‐grave environmental impacts of products and services; it is actively promoted by many public policies, and integrated as part of environmental information systems within private companies. LCA already deals with the potential biodiversity impacts of land use, but there are significant obstacles to overcome before its models grasp the full reach of the phenomena involved. In this review, we discuss some pressing issues that need to be addressed. LCA mainly introduces biodiversity as an endpoint category modeled as a loss in species richness due to the conversion and use of land over time and space. The functional and population effects on biodiversity are mostly absent due to the emphasis on species accumulation with limited geographic and taxonomical reach. Current land‐use modeling activities that use biodiversity indicators tend to oversimplify the real dynamics and complexity of the interactions of species among each other and with their habitats. To identify the main areas for improvement, we systematically reviewed LCA studies on land use that had findings related to global change and conservation ecology. We provide suggestion as to how to address some of the issues raised. Our overall objective was to encourage companies to monitor and take concrete steps to address the impacts of land use on biodiversity on a broader geographical scale and along increasingly globalized supply chains.

Global food systems contribute to climate change, the transgression of planetary boundaries and deforestation. An improved understanding of the environmental impacts of different food system futures is crucial for forging strategies to sustainably nourish a growing world population. We here quantify the greenhouse gas (GHG) emissions of global food system scenarios within a biophysically feasible "option space" in 2050 comprising all scenarios in which biomass supply - calculated as function of agricultural area and yields - is sufficient to cover biomass demand - derived from human diets and the feed demand of livestock. We assessed the biophysical feasibility of 520 scenarios in a hypothetical no-deforestation world. For all feasible scenarios, we calculate (in) direct GHG emissions related to agriculture. We also include (possibly negative) GHG emissions from land-use change, including changes in soil organic carbon (SOC) and carbon sinks from vegetation regrowth on land spared from food production. We identify 313 of 520 scenarios as feasible. Agricultural GHG emissions (excluding land use change) of feasible scenarios range from 1.7 to 12.5 Gt CO2e yr-1. When including changes in SOC and vegetation regrowth on spare land, the range is between -10.7 and 12.5 Gt CO2e yr-1. Our results show that diets are the main determinant of GHG emissions, with highest GHG emissions found for scenarios including high meat demand, especially if focused on ruminant meat and milk, and lowest emissions for scenarios with vegan diets. Contrary to frequent claims, our results indicate that diets and the composition and quantity of livestock feed, not crop yields, are the strongest determinants of GHG emissions from food-systems when existing forests are to be protected.

Soils are key resources, providing essential ecosystem services and functions for supporting both human and ecosystem needs. Intensification and expansion of human activities has been putting a dramatic pressure on land throughout history. In the last 15 years, substantial efforts have been made to incorporate the impacts on land derived from production processes from a life cycle perspective, in order to improve the comparison of the environmental performance of products. It is critical for Life Cycle Assessment (LCA) the use of robust models that enable evaluating the effects of land use on soils. The present study performs a systematic, qualitative evaluation of up-to-date models that relate land occupation and land transformation to soil impact indicators in terms of soil properties, functions and threats. We evaluated both single and multi-indicators models against criteria including scientific soundness, stakeholders’ acceptance, reproducibility, as well as the applicability of models from the perspective of LCA practitioners. The study additionally proposes a new land use cause-effect chain to appraise the impacts of land use on soils. We identified a heterogeneous set of soil-related models, with relevant improvements in terms of applicability, robustness and completeness as compared to previous analyses. Trade-offs were frequent between the relevance of the modeled impact processes and model’s applicability. We identified several research needs, which include: adopting a common land use cause-effect chain and land use classification; accounting for different land management and land use intensities; assessing the added value of multi-indicators for comprehensively account for impacts; ensuring consistency from midpoint to endpoint, especially for biodiversity impacts; providing guidance to calculate normalization factors; and assessing the uncertainty of models results. Building consensus in the LCA community is essential to secure the comparability of models and setup robust practices for further developments.JRC.D.3-Land Resource

Assessments of the global carbon (C) cycle typically rely on simplified models which consider large areas as homogeneous in terms of the response of soils to land use or consider very broad land classes. For example, “cropland” is typically modelled as an aggregation of distinct practices and individual crops over large regions. Here, we use the process-based Rothamsted soil Carbon Model (RothC model), which has a history of being successfully applied at a global scale, to calculate attainable SOC stocks and C mineralization rates for each of c. 17,000 regions (combination of soil type and texture, climate type, initial land use and country) in the World, under near-past climate conditions. We considered 28 individual crops and, for each, multiple production practices, plus 16 forest types and 1 grassland class (total of 80 classes). We find that conversion to cropland can result in SOC increases, particularly when the soil remains covered with crop residues (an average gain of 12 t C/ha) or using irrigation (4 t C/ha), which are mutually reinforcing effects. Attainable SOC stocks vary significantly depending on the land use class, particularly for cropland. Common aggregations in global modelling of a single agricultural class would be inaccurate representations of these results. Attainable SOC stocks obtained here were compared to long-term experiment data and are well aligned with the literature. Our results provide a regional and detailed understanding of C sequestration that will also enable better greenhouse gas reporting at national level as alternatives to IPCC tier 2 defaults.