Assessing uncertainties in land cover projections

Ecology needs to overcome siloed modelling

Bahlburg et al. re-implemented eight growth models of Antarctic krill and showed that their predictions are all over the place. The authors discuss the reasons for this and how more coherence in modelling could be achieved through systematic model comparison and integration. For this, we need a common language.

Benefits and trade-offs of optimizing global land use for food, water, and carbon

Current large-scale patterns of land use reflect history, local traditions, and production costs, much more so than they reflect biophysical potential or global supply and demand for food and freshwater, or-more recently-climate change mitigation. We quantified alternative land-use allocations that consider trade-offs for these demands by combining a dynamic vegetation model and an optimization algorithm to determine Pareto-optimal land-use allocations under changing climate conditions in 2090-2099 and alternatively in 2033-2042. These form the outer bounds of the option space for global land-use transformation. Results show a potential to increase all three indicators (+83% in crop production, +8% in available runoff, and +3% in carbon storage globally) compared to the current land-use configuration, with clear land-use priority areas: Tropical and boreal forests were preserved, crops were produced in temperate regions, and pastures were preferentially allocated in semiarid grasslands and savannas. Transformations toward optimal land-use patterns would imply extensive reconfigurations and changes in land management, but the required annual land-use changes were nevertheless of similar magnitude as those suggested by established land-use change scenarios. The optimization results clearly show that large benefits could be achieved when land use is reconsidered under a "global supply" perspective with a regional focus that differs across the world's regions in order to achieve the supply of key ecosystem services under the emerging global pressures.

Assessing the future global distribution of land ecosystems as determined by climate change and cropland incursion

The geographic distribution of natural ecosystems is affected by both climate and cropland. Discussions of future land use/land cover usually focus on how cropland expands and displaces natural vegetation especially as climate change impacts become stronger. Less commonly considered is the direct influence of climate change on natural ecosystems simultaneously with cropland incursion. We combine a natural vegetation model responsive to climate with a cropland allocation algorithm to assess the relative importance of climate change compared to cropland incursion. Globally, the model indicates that climate change drives larger gains and losses than cropland incursion. For example, in the Amazonian rainforests, more than one sixth of the forest area could be lost due to climate change with cropland playing virtually no role. Our findings suggest that policies to protect specific ecosystems may be undercut by climate change and that localized analyses that fully account for the impacts of a changing climate on natural vegetation and agriculture are necessary to formulate policies that preserve natural ecosystems over the long term.

Supplementary Information

The online version contains supplementary material available at 10.1007/s10584-023-03584-3.

Non-stationary evaluation of runoff peaks in response to climate variability and land use change in Ferson Creek, Illinois, USA

In this paper, we examine how surface runoff affects public safety and urban infrastructure worldwide and how human activity has significantly altered the frequency and magnitude of these events. We investigate this issue in Ferson Creek, IL, USA. Our study focuses on three specific areas of impact: (1) the primary reasons for a considerable increase in average runoff peaks, using annual maximum runoff discharge and annual maximum precipitation and temperature to evaluate the role of climate variability; (2) the effect of land use change on runoff peaks by coupling dominant land use categories with annual maximum runoff discharge; and (3) the use of return level plots as a reference to explore the watershed's sensitivity to land use change. Our findings indicate that land use change has a greater effect on runoff peak values than climate variability in our region of interest. The agricultural areas of Ferson Creek have been most affected by the rapid transformation of about 20% of their land into developed areas. Although agricultural areas can sometimes intensify runoff peaks, their reduction has led to excessive runoff discharges in Ferson Creek, as they have higher relative infiltration capacity than developed areas. We conclude that each watershed has its own fingerprint in terms of the connection between its land use types and hydrological patterns and that the region is most sensitive to the percentage of forests. These results are essential for improving infrastructure design and risk estimation methods in the region of interest.

An integrated model for prediction of hydrologic anomalies for habitat suitability of overwintering geese in a large floodplain wetland, China

Climate anomalies and increasing human activities cause a high frequency of extreme hydrological events in wetlands, which has put waterbirds under greater survival pressure than ever. Therefore, it is crucial to predict the impact of this phenomenon on the habitat suitability of waterbirds. This study investigated the response of the goose distribution probability to hydrological variations using the flood duration index (FD), enhanced vegetation index (EVI), and waterbirds GPS tracking data in Poyang Lake. An overwintering geese habitat suitability index (HSI) is built based on the FD, EVI, and threat index and verifies the accuracy of the model simulation. Then, the effects of drought and flood on the goose habitat especially sub-lakes with different connectivity were analyzed. The findings reveal that in dry and flood years, geese will broaden their range of feeding vegetation (more fresh or mature vegetation) in response to environmental deterioration. Both drought and flood can lead to a decline in the HSI, especially flood. Connected sub-lakes are more vulnerable to hydrological anomalies than controlled sub-lakes. This research establishes a scientific foundation for floodplain wetland hydrology management and waterbird conservation.

Global inventory of suitable, cultivable and available cropland under different scenarios and policies

Where land-use change and particularly the expansion of cropland could potentially take place in the future is a central research question to investigate emerging trade-offs between food security, climate protection and biodiversity conservation. We provide consistent global datasets of land potentially suitable, cultivable and available for agricultural use for historic and future time periods from 1980 until 2100 under RCP2.6 and RCP8.5, available at 30 arc-seconds spatial resolution and aggregated at country level. Based on the agricultural suitability of land for 23 globally important food, feed, fiber and bioenergy crops, and high resolution land cover data, our dataset indicates where cultivation is possible and how much land could potentially be used as cropland when biophysical constraints and different assumptions on land-use regulations are taken into account. By serving as an input for land-use models, the produced data could improve the comparability of the models and their output, and thereby contribute to a better understanding of potential land-use trade-offs.

Choices in land representation materially affect modeled biofuel carbon intensity estimates

Estimates of biofuel carbon intensity are uncertain and depend on modeled land use change (LUC) emissions. While analysts have focused on economic and agronomic assumptions affecting the quantity of land converted, researchers have paid less attention to how models classify land into broad categories and designate some categories as ineligible for LUC. To explore the effect of these land representation attributes, we use three versions of a global human and Earth systems model, GCAM, and compute the "carbon intensity of land-use change" (CI-LUC) from increased U.S. corn ethanol production. We consider uncertainty in model parameters along with the choice of land representation and find the latter is one of the most influential parameters on estimated CI-LUC. A version of the model that protects 90% of non-commercial land reduced estimated CI-LUC by an average of 32% across Monte Carlo trials compared to our baseline model. Another version that mimics the GTAP-BIO-ADV land representation, which protects all non-commercial land, reduced CI-LUC by an average of 19%. The results of this experiment demonstrate that land representation in biofuel LUC models is an important determinant of CI-LUC.

Mapping and assessment of future changes in the coastal and marine ecosystem services supply in Lithuania

Assessing and mapping ecosystem services (ES) became an integral part of coastal and marine management practices. Hence, quantitative and validated approaches are lacking, especially to address future conditions. The objective of this study is to apply further existing and develop new methodological frameworks to quantitatively assess and map the current and future supply of 3 ES in the coastal zone of Lithuania: coastal flood protection, nutrient regulation, and maintenance of nursery conditions. For coastal flood ES modelling, 2 time periods (1990 and 2018) and 4 scenarios (A0, A1 A2, A3 - based on future socio-economic changes in Lithuania) were analysed. The coastal flood protection ES model was validated (r² = 0.30) using tree cover density. The results showed spatial differences among the analysed periods but no statistical differences. High supply areas are located in the southern coastal area, while the central part displays a low supply. For nutrient regulation and maintenance of nursery conditions, 7 time periods were analysed: a historical period and 6 scenarios based on Representative Concentration Pathway 4.5 and 8.5 and 3 Shared Socioeconomic Pathways. The nutrient regulation ES model was validated (r² = 0.85) using in situ nutrient. Statistical differences were observed for this ES, but a similar spatial distribution of high and low supply areas. A decrease in the supply was observed comparing the historical period and future scenarios. Maintenance of nursery conditions was validated (r² = 0.72) based on the protection status of the coastal zone. Results show no statistical differences and similar spatial patterns among the periods. Rocky and sandbank areas show a high supply for this ES. Limitations of our work are mainly related to the resolution of the utilised indicators. Nevertheless, the information obtained from our models can support spatial planning and decision-making processes.

Projected land-use changes in the Shared Socioeconomic Pathways: Insights and implications

The conceptualization of the Shared Socioeconomic Pathways (SSPs) framework represented a major leap in scenario development in the context of global environmental change and sustainability, providing significant advances from the previous scenario frameworks-especially the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios. It is highly likely that the SSP concept, along with its scenario narratives and their respective results, including land-use change projections, will play a substantial role in the forthcoming Sixth Assessment Report by the IPCC. Here, we offer some insights that could make the SSPs' projected future changes in global land use more comprehensive and also help improve the interpretability of such projections. For example, instead of focusing on the quantity of each land-use class at various time points which results only in a net change when change is detected between time points, we recommend that the projected gross gains and gross losses in each land-use class across all scenarios should also be considered. Overall, the insights presented could also help pave the way for stronger collaboration between the SSP-climate science community and the land system science community; such collaboration is much needed in addressing the challenges of global environmental change towards a climate-resilient sustainable development pathway.

Identifying Agricultural Frontiers for Modeling Global Cropland Expansion

The increasing expansion of cropland is major driver of global carbon emissions and biodiversity loss. However, predicting plausible future global distributions of croplands remains challenging. Here, we show that, in general, existing global data aligned with classical economic theories of expansion explain the current (1992) global extent of cropland reasonably well, but not recent expansion (1992-2015). Deviations from models of cropland extent in 1992 ("frontierness") can be used to improve global models of recent expansion, most likely as these deviations are a proxy for cropland expansion under frontier conditions where classical economic theories of expansion are less applicable. Frontierness is insensitive to the land cover dataset used and is particularly effective in improving models that include mosaic land cover classes and the largely smallholder-driven frontier expansion occurring in such areas. Our findings have important implications as the frontierness approach offers a straightforward way to improve global land use change models.

Assessment of the Future Climate Change Projections on Streamflow Hydrology and Water Availability over Upper Xijiang River Basin, China

Hydrological models are widely applied for simulating complex watershed processes and directly linking meteorological, topographical, land-use, and geological conditions. In this study, the Soil and Water Assessment Tool (SWAT) was calibrated at two monitoring stations, which improved model performance and increased the reliability of flow predictions in the Upper Xijiang River Basin. This study evaluated the potential impacts of climate change on the streamflow and water yield of the Upper Xijiang River Basin using Arc-SWAT. The model was calibrated (1991–1997) and validated (1998–2001) using the Sequential Uncertainty Fitting Algorithm (SUFI-2). Model calibration and validation suggest a good match between the measured and simulated monthly streamflow, indicating the applicability of the model for future daily streamflow predictions. Large negative changes of low flows are projected under future climate scenarios, exhibiting a 10% and 30% decrease in water yield over the watershed on a monthly scale. Overall, findings generally indicated that winter flows are expected to be affected the most, with a maximum impact during the January–April period, followed by the wet monsoon season in the May–September period. Water balance components of the Upper Xijiang River Basin are expected to change significantly due to the projected climate change that, in turn, will seriously affect the water resources and streamflow patterns in the future. Thus, critical problems, such as ground water shortages, drops in agricultural crop yield, and increases in domestic water demand are expected at the Xijiang River Basin.

Quantifying the Effect of Land Use Change Model Coupling

Land-use change (LUC) is a complex process that is difficult to project. Model collaboration, an aggregate term for model harmonization, comparison and/or coupling, intends to combine the strengths of different models to improve LUC projections. Several model collaborations have been performed, but to the authors’ knowledge, the effect of coupling has not been evaluated quantitatively. Therefore, for a case study of Brazil, we harmonized and coupled the partial equilibrium model GLOBIOM-Brazil and the demand-driven spatially explicit model PLUC, and then compared the coupled-model projections with those by GLOBIOM-Brazil individually. The largest differences between projections occurred in Mato Grosso and Pará, frontiers of agricultural expansion. In addition, we validated both projections for Mato Grosso using land-use maps from remote sensing images. The coupled model clearly outperformed GLOBIOM-Brazil. Reductions in the root mean squared error (RMSE) for LUC dynamics ranged from 31% to 80% and for total land use, from 10% to 57%. Only for pasture, the coupled model performed worse in total land use (RMSE 9% higher). Reasons for a better performance of the coupled model were considered to be, inter alia, the initial map, more spatially explicit information about drivers, and the path-dependence effect in the allocation through the cellular-automata approach of PLUC.

Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios

Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1–3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by the model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritize future protection of biodiverse and carbon-rich areas.

This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.

Impacts of land use/land cover on runoff and energy budgets in an East Asia ecosystem from remotely sensed data in a community land model

The impacts of land use/land cover (LULC) conditions on the global water and energy budgets are essential to understanding climate intensification in the 21st century. This study evaluated latent heat flux (LE), sensible heat flux (H), and runoff in four climate regions (temperate, continental, arid, and tropical) in East Asia from 2001 to 2015. Two community land model (CLM) experiments were performed using default LULC data (CLM 4.0) and newly created Moderate Resolution Imaging Spectroradiometer (MODIS) based LULC data from 2010 (CLM 2010) to assess the impact of LULC changes on climate. Anthropogenic LULC changes have considerable impacts on the climate and its extremes. For the whole East Asia region, area-averaged runoff decreased by 2.10%. The temperate region experienced a 3.16% decrease in runoff and a 4.22% increase in LE due to an increase in irrigation activities that could lead to the drying of soil moisture and drought in the future. In contrast, the arid region experienced a 6.30% increase in runoff despite dry conditions and a 5.70% reduction in LE, which ultimately increased H by 2.25% and caused an intensification of the climate in the form of strong heat waves and floods. The continental region followed the same trend as the temperate region with a noticeable decrease in winter H, which caused severe cold weather. The tropical region showed a slight impact of LULC change on energy fluxes due to high precipitation and intense solar radiations. Overall, the results of this research follow the 'dry gets drier and wet gets wetter' paradigm due to LULC changes in the study region.

Global impacts of future cropland expansion and intensification on agricultural markets and biodiversity

With rising demand for biomass, cropland expansion and intensification represent the main strategies to boost agricultural production, but are also major drivers of biodiversity decline. We investigate the consequences of attaining equal global production gains by 2030, either by cropland expansion or intensification, and analyse their impacts on agricultural markets and biodiversity. We find that both scenarios lead to lower crop prices across the world, even in regions where production decreases. Cropland expansion mostly affects biodiversity hotspots in Central and South America, while cropland intensification threatens biodiversity especially in Sub-Saharan Africa, India and China. Our results suggest that production gains will occur at the costs of biodiversity predominantly in developing tropical regions, while Europe and North America benefit from lower world market prices without putting their own biodiversity at risk. By identifying hotspots of potential future conflicts, we demonstrate where conservation prioritization is needed to balance agricultural production with conservation goals.

The increase in needs for agricultural commodities is projected to outpace the growth of farmland production globally, leading to high pressure on farming systems in the next decades. Here, the authors investigate the future impact of cropland expansion and intensification on agricultural markets and biodiversity, and suggest the need for balancing agricultural production with conservation goals.

Key determinants of global land-use projections

Land use is at the core of various sustainable development goals. Long-term climate foresight studies have structured their recent analyses around five socio-economic pathways (SSPs), with consistent storylines of future macroeconomic and societal developments; however, model quantification of these scenarios shows substantial heterogeneity in land-use projections. Here we build on a recently developed sensitivity approach to identify how future land use depends on six distinct socio-economic drivers (population, wealth, consumption preferences, agricultural productivity, land-use regulation, and trade) and their interactions. Spread across models arises mostly from diverging sensitivities to long-term drivers and from various representations of land-use regulation and trade, calling for reconciliation efforts and more empirical research. Most influential determinants for future cropland and pasture extent are population and agricultural efficiency. Furthermore, land-use regulation and consumption changes can play a key role in reducing both land use and food-security risks, and need to be central elements in sustainable development strategies.

There lacks model comparison of global land use change projections. Here the authors explored how different long-term drivers determine land use and food availability projections and they showed that the key determinants population growth and improvements in agricultural efficiency.

Methods to Assess the Impacts and Indirect Land Use Change Caused by Telecoupled Agricultural Supply Chains: A Review

The increasing international trade of agricultural products has contributed to a larger diversity of food at low prices and represents an important economic value. However, such trade can also cause social, environmental and economic impacts beyond the limits of the countries directly involved in the exchange. Agricultural systems are telecoupled because the impacts caused by trade can generate important feedback loops, spillovers, rebound effects, time lags and non-linearities across multiple geographical and temporal scales that make these impacts more difficult to identify and mitigate. We make a comparative review of current impact assessment methods to analyze their suitability to assess the impacts of telecoupled agricultural supply chains. Given the large impacts caused by agricultural production on land systems, we focus on the capacity of methods to account for and spatially allocate direct and indirect land use change. Our analysis identifies trade-offs between methods with respect to the elements of the telecoupled system they address. Hybrid methods are a promising field to navigate these trade-offs. Knowledge gaps in assessing indirect land use change should be overcome in order to improve the accuracy of assessments.

Climate change-driven range losses among bumblebee species are poised to accelerate

Climate change has shaped bee distributions over the past century. Here, we conducted the first species-specific assessment of future climate change impacts on North American bumblebee distributions, using the most recent global change scenarios developed in the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC). We assessed potential shifts in bumblebee species distributions with models generated using Maxent. We tested different assumptions about bumblebee species’ dispersal capacities, drawing on observed patterns of range shifts to date, dispersal rates observed for bumblebee queens, and, lastly, assuming unlimited dispersal. Models show significant contractions of current ranges even under scenarios in which dispersal rates were high. Results suggest that dispersal rates may not suffice for bumblebees to track climate change as rapidly as required under any IPCC scenario for future climate change. Areas where species losses are projected overlap for many species and climate scenarios, and are concentrated in eastern parts of the continent. Models also show overlap for range expansions across many species, suggesting the presence of “hotspots” where management activities could benefit many species, across all climate scenarios. Broad-scale strategies are likely to be necessary to improve bumblebee conservation prospects under climate change.

Adaptation of global land use and management intensity to changes in climate and atmospheric carbon dioxide

Land use contributes to environmental change, but is also influenced by such changes. Climate and atmospheric carbon dioxide (CO₂ ) levels' changes alter agricultural crop productivity, plant water requirements and irrigation water availability. The global food system needs to respond and adapt to these changes, for example, by altering agricultural practices, including the crop types or intensity of management, or shifting cultivated areas within and between countries. As impacts and associated adaptation responses are spatially specific, understanding the land use adaptation to environmental changes requires crop productivity representations that capture spatial variations. The impact of variation in management practices, including fertiliser and irrigation rates, also needs to be considered. To date, models of global land use have selected agricultural expansion or intensification levels using relatively aggregate spatial representations, typically at a regional level, that are not able to characterise the details of these spatially differentiated responses. Here, we show results from a novel global modelling approach using more detailed biophysically derived yield responses to inputs with greater spatial specificity than previously possible. The approach couples a dynamic global vegetative model (LPJ-GUESS) with a new land use and food system model (PLUMv2), with results benchmarked against historical land use change from 1970. Land use outcomes to 2100 were explored, suggesting that increased intensity of climate forcing reduces the inputs required for food production, due to the fertilisation and enhanced water use efficiency effects of elevated atmospheric CO₂ concentrations, but requiring substantial shifts in the global and local patterns of production. The results suggest that adaptation in the global agriculture and food system has substantial capacity to diminish the negative impacts and gain greater benefits from positive outcomes of climate change. Consequently, agricultural expansion and intensification may be lower than found in previous studies where spatial details and processes consideration were more constrained.

Improving the representation of adaptation in climate change impact models

Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.

Global change and the distributional dynamics of migratory bird populations wintering in Central America

Understanding the susceptibility of highly mobile taxa such as migratory birds to global change requires information on geographic patterns of occurrence across the annual cycle. Neotropical migrants that breed in North America and winter in Central America occur in high concentrations on their non-breeding grounds where they spend the majority of the year and where habitat loss has been associated with population declines. Here, we use eBird data to model weekly patterns of abundance and occurrence for 21 forest passerine species that winter in Central America. We estimate species' distributional dynamics across the annual cycle, which we use to determine how species are currently associated with public protected areas and projected changes in climate and land-use. The effects of global change on the non-breeding grounds is characterized by decreasing precipitation, especially during the summer, and the conversion of forest to cropland, grassland, or peri-urban. The effects of global change on the breeding grounds are characterized by increasing winter precipitation, higher temperatures, and the conversion of forest to peri-urban. During spring and autumn migration, species are projected to encounter higher temperatures, forests that have been converted to peri-urban, and increased precipitation during spring migration. Based on current distributional dynamics, susceptibility to global change is characterized by the loss of forested habitats on the non-breeding grounds, warming temperatures during migration and on the breeding grounds, and declining summer rainfall on the non-breeding grounds. Public protected areas with low and medium protection status are more prevalent on the non-breeding grounds, suggesting that management opportunities currently exist to mitigate near-term non-breeding habitat losses. These efforts would affect more individuals of more species during a longer period of the annual cycle, which may create additional opportunities for species to respond to changes in habitat or phenology that are likely to develop under climate change.

Losses, inefficiencies and waste in the global food system

Losses at every stage in the food system influence the extent to which nutritional requirements of a growing global population can be sustainably met. Inefficiencies and losses in agricultural production and consumer behaviour all play a role. This paper aims to understand better the magnitude of different losses and to provide insights into how these influence overall food system efficiency. We take a systems view from primary production of agricultural biomass through to human food requirements and consumption. Quantities and losses over ten stages are calculated and compared in terms of dry mass, wet mass, protein and energy. The comparison reveals significant differences between these measurements, and the potential for wet mass figures used in previous studies to be misleading. The results suggest that due to cumulative losses, the proportion of global agricultural dry biomass consumed as food is just 6% (9.0% for energy and 7.6% for protein), and 24.8% of harvest biomass (31.9% for energy and 27.8% for protein). The highest rates of loss are associated with livestock production, although the largest absolute losses of biomass occur prior to harvest. Losses of harvested crops were also found to be substantial, with 44.0% of crop dry matter (36.9% of energy and 50.1% of protein) lost prior to human consumption. If human over-consumption, defined as food consumption in excess of nutritional requirements, is included as an additional inefficiency, 48.4% of harvested crops were found to be lost (53.2% of energy and 42.3% of protein). Over-eating was found to be at least as large a contributor to food system losses as consumer food waste. The findings suggest that influencing consumer behaviour, e.g. to eat less animal products, or to reduce per capita consumption closer to nutrient requirements, offer substantial potential to improve food security for the rising global population in a sustainable manner.