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Climate change is expected to increase fire risk in many forested regions, posing a potential threat to forest functioning (i.e. carbon pools and fluxes). At the same time, expansion of the wildland-urban interface threatens to bring more and more people, property, and infrastructure into contact with wildfire events. It is critical that fire be managed in a way that minimizes risk to human health and well-being and maintains forest climate change mitigation potential without affecting the important ecological role fire plays in many ecosystems. Dynamic global vegetation models (DGVMs) simulate processes over large geographic regions and long time periods and could provide information that supports fire and fuel management programs by assessing performance of such measures under different climate change scenarios in different regions. However, thus far DGVMs have not been put to this use. In this work, we introduce a novel prescribed burning (PB) module to the LPJ-GUESS DGVM. Focusing on two regions (Eastern Europe and the Iberian Peninsula), we compare the effectiveness of PB and mechanical thinning on various aspects of the fire regime under two climate change scenarios through the end of the 21st century. We find that PB and thinning, by reducing fuel load, reduce fireline intensity; this suggests that what wildfires do occur could be more easily controlled. While this would reduce risks to human health and well-being, PB comes with the tradeoff of increased fire emissions, which could contribute to respiratory problems. Mechanical thinning reduces fireline intensity by as much or more while also reducing emissions. While net primary production remained unaffected by fire management, cumulative net biome production until the end of the 21st century declined especially under the influence of thinning. While these results are based on stylized management treatments, this work shows the potential of DGVMs in exploring fire management options.

Abstract Future changes in solar radiation and rising temperatures will likely reduce global solar photovoltaic potential, but advancing photovoltaic technologies could counteract these effects. We investigate the potential of photovoltaic to satisfy energy demands given climate change and technological development. We find that conventional photovoltaic will require 0.5 to 1.2% of global land area to meet projected energy demands by 2085 without accounting for climate change effects. When considering climate impacts, this requirement increases to 0.7–1.5% of the global land area. However, utilising advanced photovoltaic technologies can reduce this area to 0.3–1.2%, effectively mitigating climate impacts. Regional climate change impacts vary substantially, resulting in photovoltaic potential decreases of up to 3% in Latin America and the Caribbean, and by up to 8% in South Asia. Our results suggest that technology-driven increases in future global photovoltaic energy production can more than compensate for the climate related reductions.

Supplying food for the anticipated global population of over 9 billion in 2050 under changing climate conditions is one of the major challenges of the 21st century. Agricultural expansion and intensification contributes to global environmental change and risks the long-term sustainability of the planet. It has been proposed that no more than 15% of the global ice-free land surface should be converted to cropland. Bioenergy production for land-based climate mitigation places additional pressure on limited land resources. Here we test normative targets of food supply and bioenergy production within the cropland planetary boundary using a global land-use model. The results suggest supplying the global population with adequate food is possible without cropland expansion exceeding the planetary boundary. Yet this requires an increase in food production, especially in developing countries, as well as a decrease in global crop yield gaps. However, under current assumptions of future food requirements, it was not possible to also produce significant amounts of first generation bioenergy without cropland expansion. These results suggest that meeting food and bioenergy demands within the planetary boundaries would need a shift away from current trends, for example, requiring major change in the demand-side of the food system or advancing biotechnologies.

Introduction: Insulin resistance is a common condition affecting thousands of people worldwide. This paper aims to examine the mechanisms underlying insulin resistance among people suffering from obesity. Methods and Design: This study entailed identifying articles related to insulin resistance and obesity. The publications were obtained using different electronic databases, including PubMed, EBSCO, and LILACS. The search terms included “insulin”, “resistance”, “obesity”, and “mechanisms”. Boolean operators were used to combine terms and phrases. Results: Insulin resistance is a physiological condition characterized by the impaired action of insulin in the body. The association between obesity and insulin resistance is linked to inflammatory, neural, and endocrine pathways that affect the sensitivity of organs to the level of insulin in the body. Discussion: Molecular studies have helped discover some of the fundamental mechanisms leading to the development of insulin resistance. Further investigations are needed to enhance our understanding of the connections among the inflammatory, neural, and cellular processes underlying the association between insulin resistance and obesity. Conclusion: This study revealed that a complex correlation exists between insulin resistance and obesity. This relationship involves a wide range of inflammatory, neural, and endocrine processes.

Abstract The Amazon is the largest continuous tropical forest in the world and plays a key role in the global carbon cycle. Human-induced disturbances and climate change have impacted the Amazon carbon balance. Here we conduct a comprehensive synthesis of existing state-of-the-art estimates of the contemporary land carbon fluxes in the Amazon using a set of bottom-up methods (i.e., dynamic vegetation models and bookkeeping models) and a top-down inversion (atmospheric inversion model) over the Brazilian Amazon and the whole Biogeographical Amazon domain. Over the whole biogeographical Amazon region bottom-up methodologies suggest a small average carbon sink over 2010-2020, in contrast to a small carbon source simulated by top-down inversion (2010-2018). However, these estimates are not significantly different from one another when accounting for their large individual uncertainties, highlighting remaining knowledge gaps, and the urgent need to reduce such uncertainties. Nevertheless, both methodologies agreed that the Brazilian Amazon has been a net carbon source during recent climate extremes and that the south-eastern Amazon was a net land carbon source over the whole study period (2010-2020). Overall, our results point to increasing human-induced disturbances (deforestation and forest degradation by wildfires) and reduction in the old-growth forest sink during drought.

Liver cancer represents a substantial global health challenge, contributing significantly to worldwide morbidity and mortality. It has long been understood that tumors are not composed solely of cancerous cells, but also include a variety of normal cells within their structure. These tumor-associated normal cells encompass vascular endothelial cells, fibroblasts, and various inflammatory cells, including neutrophils, monocytes, macrophages, mast cells, eosinophils, and lymphocytes. Additionally, tumor cells engage in complex interactions with stromal cells and elements of the extracellular matrix (ECM). Initially, the components of what is now known as the tumor microenvironment (TME) were thought to be passive bystanders in the processes of tumor proliferation and local invasion. However, recent research has significantly advanced our understanding of the TME’s active role in tumor growth and metastasis. Tumor progression is now known to be driven by an intricate imbalance of positive and negative regulatory signals, primarily influenced by specific growth factors produced by both inflammatory and neoplastic cells. This review article explores the latest developments and future directions in understanding how the TME modulates liver cancer, with the aim of informing the design of novel therapies that target critical components of the TME.

Multiple sclerosis (MS) is a disease of the central nervous system (CNS) characterized by inflammation and autoimmune responses. This review explores the participation of T cells, particularly certain CD3+CD20+ T cells, in the clinical manifestations of MS and highlights their presence in diagnosed patients. These T cells show aberrant expression of CD20, normally considered a B-cell marker. In this review, relevant journal articles available in PubMed and CINAHL were identified by employing diverse search terms, such as MS, CD3+CD20+ T cells, the incidence and significance of CD3+CD20+ T cells in MS patients, and the impact of rituximab treatment. The search was limited to articles published in the ten-year period from 2014 to 2024. The results of this review suggest that most scholars agree on the presence of CD3+CD20+ T cells in cerebrospinal fluid. Emerging concepts relate to the fundamental role of CD20-expressing T cells in determining the target and efficacy of MS therapeutics and the presence of T cells in the cerebrospinal fluid of MS patients. The results clearly show that CD20+ T cells indicate disease chronicity and high disease activity.

The two most urgent and interlinked environmental challenges humanity faces are climate change and biodiversity loss. We are entering a pivotal decade for both the international biodiversity and climate change agendas with the sharpening of ambitious strategies and targets by the Convention on Biological Diversity and the United Nations Framework Convention on Climate Change. Within their respective Conventions, the biodiversity and climate interlinked challenges have largely been addressed separately. There is evidence that conservation actions that halt, slow or reverse biodiversity loss can simultaneously slow anthropogenic mediated climate change significantly. This review highlights conservation actions which have the largest potential for mitigation of climate change. We note that conservation actions have mainly synergistic benefits and few antagonistic trade-offs with climate change mitigation. Specifically, we identify direct co-benefits in 14 out of the 21 action targets of the draft post-2020 global biodiversity framework of the Convention on Biological Diversity, notwithstanding the many indirect links that can also support both biodiversity conservation and climate change mitigation. These relationships are context and scale-dependent; therefore, we showcase examples of local biodiversity conservation actions that can be incentivized, guided and prioritized by global objectives and targets. The close interlinkages between biodiversity, climate change mitigation, other nature's contributions to people and good quality of life are seldom as integrated as they should be in management and policy. This review aims to re-emphasize the vital relationships between biodiversity conservation actions and climate change mitigation in a timely manner, in support to major Conferences of Parties that are about to negotiate strategic frameworks and international goals for the decades to come.

It is over three decades since a large terrestrial carbon sink ( S _T ) was first reported. The magnitude of the net sink is now relatively well known, and its importance for dampening atmospheric CO _2 accumulation, and hence climate change, widely recognised. But the contributions of underlying processes are not well defined, particularly the role of emissions from land-use change ( E _LUC ) versus the biospheric carbon uptake ( S _L ; S _T = S _L − E _LUC ). One key aspect of the interplay of E _LUC and S _L is the role of agricultural processes in land-use change emissions, which has not yet been clearly quantified at the global scale. Here we assess the effect of representing agricultural land management in a dynamic global vegetation model. Accounting for harvest, grazing and tillage resulted in cumulative E _LUC since 1850 ca. 70% larger than in simulations ignoring these processes, but also changed the timescale over which these emissions occurred and led to underestimations of the carbon sequestered by possible future reforestation actions. The vast majority of Earth system models in the recent IPCC Fifth Assessment Report omit these processes, suggesting either an overestimation in their present-day S _T , or an underestimation of S _L , of up to 1.0 Pg C a ^−1 . Management processes influencing crop productivity per se are important for food supply, but were found to have little influence on E _LUC .

Specific critical functions of endocrine and immune cells ensure that an individual remains healthy and free from infection. This study aimed to explore immune–endocrine associations involved in disease. Methods: The PsycINFO, PubMed, Web of Science, and CINAHL databases were searched for relevant articles using the following search terms and phrases: “hormones”, “hormonal responses”, “immune system”, “endocrine system”, “infection”, “immune cells”, “endocrine cells”, “infection”, “immune”, “endocrine”, and “interactions”. The search was limited to articles published between 2009 and 2023. Results: A review of ninety-three studies showed that metabolic activity levels in the body as well as energy consumption patterns are affected by feedback loops that connect the endocrine and immune systems. The associations between endocrine cells and immune cells are complex and involve a wide range of hormones, molecules, and receptors related to antipathogen responses and metabolic regulation. Conclusions: During infection, endocrine cells and immune cells interact via feedback loops to ensure optimal energy utilization and a timely response to pathogens. Therefore, the endocrine system helps to regulate systemic metabolism while controlling the outcomes of regulatory elements of the immune system.

Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision.

Monocytes play a critical role in the initiation and progression of multiple sclerosis (MS). Recent research indicates the importance of considering the roles of monocytes in the management of MS and the development of effective interventions. This systematic review examined published research on the roles of nonclassical monocytes in MS and how they influence disease management. Reputable databases, such as PubMed, EMBASE, Cochrane, and Google Scholar, were searched for relevant studies on the influence of monocytes on MS. The search focused on studies on humans and patients with experimental autoimmune encephalomyelitis (EAE) published between 2014 and 2024 to provide insights into the study topic. Fourteen articles that examined the role of monocytes in MS were identified; the findings reported in these articles revealed that nonclassical monocytes could act as MS biomarkers, aid in the development of therapeutic interventions, reveal disease pathology, and improve approaches for monitoring disease progression. This review provides support for the consideration of monocytes when researching effective diagnostics, therapeutic interventions, and procedures for managing MS pathophysiology. These findings may guide future research aimed at gaining further insights into the role of monocytes in MS.

We have investigated the spatio-temporal carbon balance patterns resulting from forcing a dynamic global vegetation model with output from 18 climate models of the CMIP5 (Coupled Model Intercomparison Project Phase 5) ensemble. We found robust patterns in terms of an extra-tropical loss of carbon, except for a temperature induced shift in phenology, leading to an increased spring uptake of carbon. There are less robust patterns in the tropics, a result of disagreement in projections of precipitation and temperature. Although the simulations generally agree well in terms of the sign of the carbon balance change in the middle to high latitudes, there are large differences in the magnitude of the loss between simulations. Together with tropical uncertainties these discrepancies accumulate over time, resulting in large differences in total carbon uptake over the coming century (−0.97–2.27 Pg C yr ^−1 during 2006–2100). The terrestrial biosphere becomes a net source of carbon in ten of the 18 simulations adding to the atmospheric CO _2 concentrations, while the remaining eight simulations indicate an increased sink of carbon.

Nitrous oxide (N2O), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric N2O concentrations have contributed to stratospheric ozone depletion1 and climate change2, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of N2O emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources. Here we present a global N2O inventory that incorporates both natural and anthropogenic sources and accounts for the interaction between nitrogen additions and the biochemical processes that control N2O emissions. We use bottom-up (inventory, statistical extrapolation of flux measurements, process-based land and ocean modelling) and top-down (atmospheric inversion) approaches to provide a comprehensive quantification of global N2O sources and sinks resulting from 21 natural and human sectors between 1980 and 2016. Global N2O emissions were 17.0 (minimum-maximum estimates: 12.2-23.5) teragrams of nitrogen per year (bottom-up) and 16.9 (15.9-17.7) teragrams of nitrogen per year (top-down) between 2007 and 2016. Global human-induced emissions, which are dominated by nitrogen additions to croplands, increased by 30% over the past four decades to 7.3 (4.2-11.4) teragrams of nitrogen per year. This increase was mainly responsible for the growth in the atmospheric burden. Our findings point to growing N2O emissions in emerging economies-particularly Brazil, China and India. Analysis of process-based model estimates reveals an emerging N2O-climate feedback resulting from interactions between nitrogen additions and climate change. The recent growth in N2O emissions exceeds some of the highest projected emission scenarios3,4, underscoring the urgency to mitigate N2O emissions.

Land biosphere processes are of central importance to the climate system. Specifically, ecosystems interact with the atmosphere through a variety of feedback loops that modulate energy, water, and CO2 fluxes between the land surface and the atmosphere across a wide range of temporal and spatial scales. Human land use and land cover modification add a further level of complexity to land–atmosphere interactions. Dynamic global vegetation models (DGVMs) attempt to capture land ecosystem processes and are increasingly incorporated into Earth system models (ESMs), which makes it possible to study the coupled dynamics of the land biosphere and the climate. In this work we describe a number of modifications to the LPJ-GUESS DGVM, aimed at enabling direct integration into an ESM. These include energy balance closure, the introduction of a sub-daily time step, a new radiative transfer scheme, and improved soil physics. The implemented modifications allow the model (LPJ-GUESS/LSM) to simulate the diurnal exchange of energy, water, and CO2 between the land ecosystem and the atmosphere and thus provide surface boundary conditions to an atmospheric model over land. A site-based evaluation against FLUXNET2015 data shows reasonable agreement between observed and modelled sensible and latent heat fluxes. Differences in predicted ecosystem function between standard LPJ-GUESS and LPJ-GUESS/LSM vary across land cover types. We find that the emerging ecosystem composition and carbon fluxes are sensitive to both the choice of stomatal conductance model and the response of plant water uptake to soil moisture. The new implementation described in this work lays the foundation for using the well-established LPJ-GUESS DGVM as an alternative land surface model (LSM) in coupled land–biosphere–climate studies, where an accurate representation of ecosystem processes is essential.

Understanding uncertainties and sensitivities of projected ecosystem dynamics under environmental change is of immense value for research and climate change policy. Here, we analyze sensitivities (change in model outputs per unit change in inputs) and uncertainties (changes in model outputs scaled to uncertainty in inputs) of vegetation dynamics under climate change, projected by a state-of-the-art dynamic vegetation model (LPJ-GUESS v4.0) across European forests (the species Picea abies, Fagus sylvatica and Pinus sylvestris), considering uncertainties of both model parameters and environmental drivers. We find that projected forest carbon fluxes are most sensitive to photosynthesis-, water-, and mortality-related parameters, while predictive uncertainties are dominantly induced by environmental drivers and parameters related to water and mortality. The importance of environmental drivers for predictive uncertainty increases with increasing temperature. Moreover, most of the interactions of model inputs (environmental drivers and parameters) are between environmental drivers themselves or between parameters and environmental drivers. In conclusion, our study highlights the importance of environmental drivers not only as contributors to predictive uncertainty in their own right but also as modifiers of sensitivities and thus uncertainties in other ecosystem processes. Reducing uncertainty in mortality-related processes and accounting for environmental influence on processes should therefore be a focus in further model development.

Liver cancer represents a substantial global health challenge, contributing significantly to worldwide morbidity and mortality. It has long been understood that tumors are not composed solely of cancerous cells, but also include a variety of normal cells within their structure. These tumor-associated normal cells encompass vascular endothelial cells, fibroblasts, and various inflammatory cells, including neutrophils, monocytes, macrophages, mast cells, eosinophils, and lymphocytes. Additionally, tumor cells engage in complex interactions with stromal cells and elements of the extracellular matrix (ECM). Initially, the components of what is now known as the tumor microenvironment (TME) were thought to be passive bystanders in the processes of tumor proliferation and local invasion. However, recent research has significantly advanced our understanding of the TME's active role in tumor growth and metastasis. Tumor progression is now known to be driven by an intricate imbalance of positive and negative regulatory signals, primarily influenced by specific growth factors produced by both inflammatory and neoplastic cells. This review article explores the latest developments and future directions in understanding how the TME modulates liver cancer, with the aim of informing the design of novel therapies that target critical components of the TME. [ABSTRACT FROM AUTHOR]

Multiple sclerosis (MS) is a disease of the central nervous system (CNS) characterized by inflammation and autoimmune responses. This review explores the participation of T cells, particularly certain CD3+CD20+ T cells, in the clinical manifestations of MS and highlights their presence in diagnosed patients. These T cells show aberrant expression of CD20, normally considered a B-cell marker. In this review, relevant journal articles available in PubMed and CINAHL were identified by employing diverse search terms, such as MS, CD3+CD20+ T cells, the incidence and significance of CD3+CD20+ T cells in MS patients, and the impact of rituximab treatment. The search was limited to articles published in the ten-year period from 2014 to 2024. The results of this review suggest that most scholars agree on the presence of CD3+CD20+ T cells in cerebrospinal fluid. Emerging concepts relate to the fundamental role of CD20-expressing T cells in determining the target and efficacy of MS therapeutics and the presence of T cells in the cerebrospinal fluid of MS patients. The results clearly show that CD20+ T cells indicate disease chronicity and high disease activity. [ABSTRACT FROM AUTHOR]

Simple Summary: This review explores the potential of human defensins, particularly HBD-1, in combating colorectal cancer (CRC) initiation and progression. Highlighting the need for early detection and novel CRC therapies, it examines HBD-1's ability to inhibit the mTOR pathway, a key regulator of cell growth, positioning defensin-based treatments as a promising approach with evidence for suppressing cancer cell proliferation and tumor growth. Colorectal cancer (CRC) represents a significant global healthcare burden, with a particularly concerning rising incidence among younger adults. This trend may highlight potential links between diet, gut microbiome, and CRC risk. Novel therapeutic options have been increasingly based on the understanding of molecular mechanisms and pathways. The PI3K/AKT/mTOR pathway, a crucial cell growth regulator, offers a promising target for CRC therapy. mTOR, a key component within this pathway, controls cell growth, survival, and metabolism. Understanding the specific roles of defensins, particularly human β-Defensin 1 (HBD-1), in CRC is crucial. HBD-1 exhibits potent antimicrobial activity and may influence CRC development. Deciphering defensin expression patterns in CRC holds the promise of improved understanding of tumorigenesis, which may pave the way for improved diagnostics and therapies. This article reviews recent advances in understanding regarding how HBD-1 influences CRC initiation and progression, highlighting the molecular mechanisms by which it impacts CRC. Further, we describe the interaction between defensins and mTOR pathway in CRC. [ABSTRACT FROM AUTHOR]

The unprecedented use of Earth's resources by humans, in combination with increasing natural variability in natural processes over the past century, is affecting the evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g. climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. Our understanding of these interactions and feedback between human and natural systems has been formalized through a variety of modelling approaches. However, a common conceptual framework or set of guidelines to model human-natural-system feedbacks is lacking. The presented research lays out a conceptual framework that includes representing model coupling configuration in combination with the frequency of interaction and coordination of communication between coupled models. Four different approaches used to couple representations of the human and natural system are presented in relation to this framework, which vary in the processes represented and in the scale of their application. From the development and experience associated with the four models of coupled human-natural systems, the following eight lessons were identified that if taken into account by future coupled human-natural-systems model developments may increase their success: (1) leverage the power of sensitivity analysis with models, (2) remember modelling is an iterative process, (3) create a common language, (4) make code open-access, (5) ensure consistency, (6) reconcile spatio-temporal mismatch, (7) construct homogeneous units, and (8) incorporating feedback increases non-linearity and variability. Following a discussion of feedbacks, a way forward to expedite model coupling and increase the longevity and interoperability of models is given, which suggests the use of a wrapper container software, a standardized applications programming interface (API), the incorporation of standard names, the mitigation of sunk costs by creating interfaces to multiple coupling frameworks, and the adoption of reproducible workflow environments to wire the pieces together.

An integrated understanding of the biogeochemical consequences of climate extremes and land use changes is needed to constrain land-surface feedbacks to atmospheric CO2 from associated climate change. Past assessments of the global carbon balance have shown particularly high uncertainty in Southeast Asia. Here, we use a combination of model ensembles to show that intensified land use change made Southeast Asia a strong source of CO2 from the 1980s to 1990s, whereas the region was close to carbon neutral in the 2000s due to an enhanced CO2 fertilization effect and absence of moderate-to-strong El Niño events. Our findings suggest that despite ongoing deforestation, CO2 emissions were substantially decreased during the 2000s, largely owing to milder climate that restores photosynthetic capacity and suppresses peat and deforestation fire emissions. The occurrence of strong El Niño events after 2009 suggests that the region has returned to conditions of increased vulnerability of carbon stocks.

Abstract. The unprecedented use of Earth's resources by humans, in combination with the increasing natural variability in natural processes over the past century, is affecting evolution of the Earth system. To better understand natural processes and their potential future trajectories requires improved integration with and quantification of human processes. Similarly, to mitigate risk and facilitate socio-economic development requires a better understanding of how the natural system (e.g., climate variability and change, extreme weather events, and processes affecting soil fertility) affects human processes. To capture and formalize our understanding of the interactions and feedback between human and natural systems a variety of modelling approaches are used. While integrated assessment models are widely recognized as supporting this goal and integrating representations of the human and natural system for global applications, an increasing diversity of models and corresponding research have focused on coupling models specializing in specific human (e.g., decision-making) or natural (e.g., erosion) processes at multiple scales. Domain experts develop these specialized models with a greater degree of detail, accuracy, and transparency, with many adopting open-science norms that use new technology for model sharing, coupling, and high performance computing. We highlight examples of four different approaches used to couple representations of the human and natural system, which vary in the processes represented and in the scale of their application. The examples illustrate how groups of researchers have attempted to overcome the lack of suitable frameworks for coupling human and natural systems to answer questions specific to feedbacks between human and natural systems. We draw from these examples broader lessons about system and model coupling and discuss the challenges associated with maintaining consistency across models and representing feedback between human and natural systems in coupled models.