The achievement of several sustainable development goals and the Paris Climate Agreement depends on rapid progress towards sustainable food and land systems in all countries. We have built a flexible, collaborative modeling framework to foster the development of national pathways by local research teams and their integration up to global scale. Local researchers independently customize national models to explore mid-century pathways of the food and land use system transformation in collaboration with stakeholders. An online platform connects the national models, iteratively balances global exports and imports, and aggregates results to the global level. Our results show that actions toward greater sustainability in countries could sum up to 1 Mha net forest gain per year, 950 Mha net gain in the land where natural processes predominate, and an increased CO 2 sink of 3.7 GtCO 2 e yr −1 over the period 2020–2050 compared to current trends, while average food consumption per capita remains above the adequate food requirements in all countries. We show examples of how the global linkage impacts national results and how different assumptions in national pathways impact global results. This modeling setup acknowledges the broad heterogeneity of socio-ecological contexts and the fact that people who live in these different contexts should be empowered to design the future they want. But it also demonstrates to local decision-makers the interconnectedness of our food and land use system and the urgent need for more collaboration to converge local and global priorities.

The development of detailed national pathways towards sustainable food and land systems aims to provide stakeholders with clarity on how long-term goals could be achieved and to reduce roadblocks in the way to making commitments. However, the inability to perfectly capture the relationships between all variables in a system and the unknown probability of future values (deep uncertainty) makes it very difficult to design scenarios that account for the full breadth of system uncertainty. Here we use scenario discovery to systematically explore the effect of different parameter ranges on model outputs, and design resilient pathways to sustainability in which multiple target achievement requires a broad portfolio of solutions. We use a model of the Australian food and land system, the FABLE (Food, Agriculture, Biodiversity, Land-use, Energy) Calculator, to investigate conditions for achieving a sustainable Australian food and land system under scenarios based on the Shared Socioeconomic Pathways (SSP) 1, 2, and 3 narratives. Here we link the FABLE Calculator with a Monte Carlo simulation tool to explore hundreds of thousands of scenarios. This allows us to identify the ranges of systemic drivers that achieve multiple sustainability targets around diets, net forest growth, agricultural water consumption, greenhouse gas emissions, biodiversity conservation, and exports by 2050. Our results show that livestock productivity and density, afforestation, and dietary change are powerful influencers for sustainability target achievement. Around 10% of the SSP1 scenarios could achieve all modelled sustainability targets. However, practically none of the scenarios based on SSP2 and SSP3 narratives could achieve such targets. The results suggest that there are options to achieve a more sustainable and resilient Australian food and land-use system with better socio-economic and environmental outcomes than under current trends. However, its achievement requires significant structural changes and coordinated interventions in several components of the domestic food and land system to increase its resilience and environmental and socio-economic performance. Understanding the bounds within which this system needs to change and operate to achieve sustainability targets will enable greater clarity and flexibility during discussions between decision-makers and stakeholders.

There is an urgent need for countries to transition their national food and land-use systems toward food and nutritional security, climate stability, and environmental integrity. How can countries satisfy their demands while jointly delivering the required transformative change to achieve global sustainability targets? Here, we present a collaborative approach developed with the FABLE-Food, Agriculture, Biodiversity, Land, and Energy-Consortium to reconcile both global and national elements for developing national food and land-use system pathways. This approach includes three key features: (1) global targets, (2) country-driven multi-objective pathways, and (3) multiple iterations of pathway refinement informed by both national and international impacts. This approach strengthens policy coherence and highlights where greater national and international ambition is needed to achieve global goals (e.g., the SDGs). We discuss how this could be used to support future climate and biodiversity negotiations and what further developments would be needed.

Villager is an agent-based modeling framework: it prescribes a convention and interface for modelers to create and run agent-based models (ABM).The framework is aimed at researchers in the social sciences who are focused on modeling human populations.The key features of villager are:1. Scalability: villager makes extensive use of the R6 class system (Chang, 2020), enabling the power of reference semantics without the hurdles of manual memory management.This enabled an architecture design where user-supplied functions are run within the framework.The reference semantics also enable cheaper memory operations by allowing for the mutation of agents in-place rather than costly copy semantics.2. Extensibility: villager exposes a number of classes that can be extended by domain scientists to provide flexibility in experiment design.The extended classes can be "plugged" into the villager framework and run seamlessly.Together, these two features allow researchers to design ABMs with flexible requirements-both functionally and computationally.

The remaining carbon budget for limiting global warming to 1.5 degrees Celsius will probably be exhausted within this decade1,2. Carbon debt3 generated thereafter will need to be compensated by net-negative emissions4. However, economic policy instruments to guarantee potentially very costly net carbon dioxide removal (CDR) have not yet been devised. Here we propose intertemporal instruments to provide the basis for widely applied carbon taxes and emission trading systems to finance a net-negative carbon economy5. We investigate an idealized market approach to incentivize the repayment of previously accrued carbon debt by establishing the responsibility of emitters for the net removal of carbon dioxide through 'carbon removal obligations' (CROs). Inherent risks, such as the risk of default by carbon debtors, are addressed by pricing atmospheric CO2 storage through interest on carbon debt. In contrast to the prevailing literature on emission pathways, we find that interest payments for CROs induce substantially more-ambitious near-term decarbonization that is complemented by earlier and less-aggressive deployment of CDR. We conclude that CROs will need to become an integral part of the global climate policy mix if we are to ensure the viability of ambitious climate targets and an equitable distribution of mitigation efforts across generations.

Integrated assessment models (IAMs) are analytical frameworks that combine computer models of physical and socioeconomic phenomena to provide insights on their interactions. There are two major classes of IAMs, CB‐IAMs and DP‐IAMs. CB‐IAMs are highly reduced representations of socioeconomic and climate sectors used for cost–benefit analyses of economic growth balanced against future economic damage due to climate change. DP‐IAMs are higher‐complexity models used to determine pathways to future greenhouse gas mitigation targets, or analyze the impacts of environmental change on the sectors they represent. IAMs play a central role in the economic, social, and political science of climate change research and policymaking. Ensuring geographical variation and connectivity is properly incorporated into IAMs is an important challenge.

The rise and decline of many complex, pre-European maize-farming cultures in the American Southwest coincides with the warm, climatically quiescent Medieval Climate Anomaly (MCA, ca. 850-1350 CE) and transition to the cool, hydrologically variable Little Ice Age (LIA, ca. 1350-1850 CE). The effects of drought on early subsistence agriculture in the Southwest is well studied, but the impact of temperature stress and variability on the growth of maize crops and which areas were most resilient to such stress remain open questions. We statistically downscaled outputs from a paleo-climate model experiment (CESM1 LME) to map changes to cumulative growing degree days for maize (GDD, 30/10 degrees C) and precipitation over Utah between 850 and 1449 CE, and downscaled GDD changes to local Fremont Culture archaeological site occupations from radiocarbon-dated contexts mapped as spatially discrete kernel density estimates of summed probability distributions (SPDs). We then analyzed correspondences between Fremont SPDs and GDD/precipitation between 850 and 1449 CE. In general, we found (1) high Fremont occupation intensity coincident with GDD that is less volatile than the long term average, and low occupation intensity coincident with, or following, periods of volatile GDD; (2) intensified occupation of high-elevation sites during the MCA, followed by a retreat to lower elevation sites coincident with a sudden rise in annual temperature volatility and increasing drought conditions; and (3) these occupation changes occurred in spite of the greater temperatures and variability in GDD at low-elevation sites. We found evidence that increased inter-annual variability of growing seasons prior to the onset of the LIA, was likely a determinant of Fremont subsistence strategy decision making, and high-elevation site occupation. The most resilient Fremont occupations in the face of these challenges were sited where growing season lengths were least variable.

Despite repeated calls for greater collaboration between physical and human geographers, the unique interdisciplinary potential of geography remains largely underutilized. Yet geographers are well positioned to take a leading role in the interdisciplinary turn in climate‐related research. This paper explores the possibilities for physical and human geographers to collaborate within and beyond the discipline, specifically on the topic of climate modeling. We first examine geographical research critically examining the production and circulation of climate knowledge. Drawing on insights from a recent literature called “Critical Physical Geography,” we then outline how geographers might engage in collaborative and interdisciplinary work in order to promote more democratic practices of producing climate knowledge, enrich understandings of climate change, and more effectively serve goals of social and environmental justice. We argue that both the discipline of geography and the field of climate research stand to gain enormously from geographers' efforts to talk across the divide between social and natural science within and beyond the boundaries of geography.

The Fremont were members of an expansive maize-based Ancestral Puebloan (AP) cultural complex who disappeared from Utah between the 12th and 13th centuries CE. This period brackets that of a climatic transition in the Southwest from the warm, dry Medieval Climate Anomaly (MCA, ca. 850–1350 CE) to the cool, hydro-climatically variable Little Ice Age (LIA, ca. 1350–1850 CE). We simulated maize (Zea mays) crop productivity for Fremont AP archaeological sites in Utah between 850 and 1449 CE using a process-based crop model driven by climatologies from a statistically downscaled a climate model. We compared the model-simulated crop yields to time-series of archaeological site occupations given by spatially discrete, chronologically summed probability distributions (SPDs) of radiocarbon-dated Fremont artifacts. We found that the anomalous abandonment of different sites throughout Utah may be explained by site-specific combinations of reduced mean yield due to volatile year-to-year yields caused by increasing temperature variability, increasing hydro-climatic variability, and loss of soil quality, which depended on crop management strategy. In other words, we model the elimination of the Fremont AP ecological niche by exogenous influences of temperature and precipitation variability at the MCA-LIA transition and endogenous degradation of soil from organic carbon and nitrogen loss. Our method has broad applicability to contexts of low-technology, dryland farming human-environmental interactions.

The American Southwest has experienced a series of severe droughts interspersed with strong wet episodes over the past decades, prompting questions about future climate patterns and potential intensification of weather disruptions under warming conditions. Here we show that interannual hydroclimatic variability in this region has displayed a significant level of non-stationarity over the past millennium. Our tree ring-based analysis of past drought indicates that the Little Ice Age (LIA) experienced high interannual hydroclimatic variability, similar to projections for the 21st century. This is contrary to the Medieval Climate Anomaly (MCA), which had reduced variability and therefore may be misleading as an analog for 21st century warming, notwithstanding its warm (and arid) conditions. Given past non-stationarity, and particularly erratic LIA, a 'warm LIA' climate scenario for the coming century that combines high precipitation variability (similar to LIA conditions) with warm and dry conditions (similar to MCA conditions) represents a plausible situation that is supported by recent climate simulations. Our comparison of tree ring-based drought analysis and records from the tropical Pacific Ocean suggests that changing variability in El Niño Southern Oscillation (ENSO) explains much of the contrasting variances between the MCA and LIA conditions across the American Southwest. Greater ENSO variability for the 21st century could be induced by a decrease in meridional sea surface temperature gradient caused by increased greenhouse gas concentration, as shown by several recent climate modeling experiments. Overall, these results coupled with the paleo-record suggests that using the erratic LIA conditions as benchmarks for past hydroclimatic variability can be useful for developing future water-resource management and drought and flood hazard mitigation strategies in the Southwest.