Table of contents

In 2012 Environmental Research Letters (ERL) launched a focus series of research papers on the theme of biodiversity, health and well-being. It was the year of the second Rio Summit on Sustainable Development, a huge number of species had been made extinct and conservationists were making increasingly urgent calls for the protection of biodiversity. The situation is ever more critical. Since we started the issue more species have become extinct, and hundreds more have now become critically endangered. The focus issue highlighted the complexity of the links of biodiversity and health, and provides more evidence for the importance to human health of biodiversity on our planet. Research papers contrasted anthropocentric western scientific views of biodiversity and its ecosystem service to humans, with the more horizontal conceptions of indigenous communities in the Amazon—and as many cultures have recognized throughout history, they recognize that we are part of nature: nature does not exist for us.

Recent years have witnessed unprecedented interest in how the burning of fossil fuels may impact on the global climate system. Such visibility of this issue is in part due to the increasing frequency of key international summits to debate emissions levels, including the 2015 21st Conference of Parties meeting in Paris. In this perspective we plot a timeline of significant climate meetings and reports, and against metrics of atmospheric greenhouse gas changes and global temperature. One powerful metric is cumulative CO₂ emissions that can be related to past and future warming levels. That quantity is analysed in detail through a set of papers in this ERL focus issue. We suggest it is an open question as to whether our timeline implies a lack of progress in constraining climate change despite multiple recent keynote meetings—or alternatively—that the increasing level of debate is encouragement that solutions will be found to prevent any dangerous warming levels?

This paper presents an overview of the state of measurement and monitoring capabilities for forests in the context of REDD+ needs, with a focus on what is currently possible, where improvements are needed, and what capabilities will be advanced in the near-term with new technologies already under development. We summarize the role of remote sensing (both satellite and aircraft) for observational monitoring of forests, including measuring changes in their current and past extent for setting baselines, their carbon stock density for estimating emissions in areas that are deforested or degraded, and their regrowth dynamics following disturbance. We emphasize the synergistic role of integrating field inventory measurements with remote sensing for best practices in monitoring, reporting and verification. We also address the potential of remote sensing for enforcing safeguards on conservation of natural forests and biodiversity. We argue that capabilities exist now to meet operational needs for REDD+ measurement, reporting, and verification and reference levels. For some other areas of importance for REDD+, such as safeguards for natural forests and biodiversity, monitoring capabilities are approaching operational in the near term. For all REDD+ needs, measurement capabilities will rapidly advance in the next few years as a result of new technology as well as advances in capacity building both within and outside of the tropical forest nations on which REDD+ is primarily focused.

In this work we analyse the evolution of the vulnerability concept in the research streams of climate change adaptation (CCA) and disaster risk reduction (DRR). We combine a traditional literature review with data mining procedures applied to bibliographic databases to reconstruct the history of the concept within various research topics, showing its evolution and convergences over time. To do that, we integrate different methods combining machine learning algorithms with network and cluster analyses to examine a set of 3757 articles, analysing their distinctive features and similarities on the basis of their contents as well as co-authorships. Bibliometric analyses enable the identification of different communities of articles, pinpointing key papers and authors, while literature review makes it possible to assess the concept of vulnerability evolved within and beyond research communities and scientific networks. Moreover, this work examines the role played by documents published by UN institutions (UNDRO, UNISDR, IPCC) in contributing to the evolution of vulnerability and related concepts. Results show that signs of convergence are evident between the two research streams, and that the IPCC reports have played a major role in proposing solutions for unifying definitions of vulnerability. We observe that the phases of preparation of the IPCC reports are very rich in methodological and terminological developments, while after publication, the literature shows evident signs of propagation of the proposed concepts. The DRR research stream developed before the research stream on CCA, but the latter flourished rapidly and became much larger in terms of number of publications. Nevertheless, in terms of contents, adaptation studies and the IPCC have shown increasing adoption of the concepts developed within the disaster research stream, in particular with regard to the interpretation of vulnerability as one of the dimensions of risk.

The gendered dimensions of climate change have received increasing interest in climate change adaptation, resilience, and vulnerability (ARV) research. Yet concerns have been expressed that engagement with 'gender' in this work has been tokenistic. In this context, we ask: how is climate change ARV research engaging with gender? To answer this question, we develop an assessment framework capturing key attributes of engagement and use it to evaluate peer reviewed ARV articles with a focus on gender published since 2006 (n = 123). Results indicate an increase in ARV studies with a gender focus over this period, with the level of gender engagement also increasing. There are a relatively equal numbers of studies categorized as engaging gender at a high, medium, and low level, with studies from Sub-Saharan Africa consistently exhibiting high levels of gender engagement. Gender focused ARV has a strong focus on examining female experiences, with few studies explicitly focusing on men, and no work accounting for those identifying outside the gender binary.

Soil organic matter (SOM) is an important natural resource. It is fundamental to soil and ecosystem functions across a wide range of scales, from site-specific soil fertility and water holding capacity to global biogeochemical cycling. It is also a highly complex material that is sensitive to direct and indirect human impacts. In SOM research, simulation models play an important role by providing a mathematical framework to integrate, examine, and test the understanding of SOM dynamics. Simulation models of SOM are also increasingly used in more 'applied' settings to evaluate human impacts on ecosystem function, and to manage SOM for greenhouse gas mitigation, improved soil health, and sustainable use as a natural resource. Within this context, there is a need to maintain a robust connection between scientific developments in SOM modeling approaches and SOM model applications. This need forms the basis of this review. In this review we first provide an overview of SOM modeling, focusing on SOM theory, data-model integration, and model development as evidenced by a quantitative review of SOM literature. Second, we present the landscape of SOM model applications, focusing on examples in climate change policy. We conclude by discussing five areas of recent developments in SOM modeling including: (1) microbial roles in SOM stabilization; (2) modeling SOM saturation kinetics; (3) temperature controls on decomposition; (4) SOM dynamics in deep soil layers; and (5) SOM representation in earth system models. Our aim is to comprehensively connect SOM model development to its applications, revealing knowledge gaps in need of focused interdisciplinary attention and exposing pitfalls that, if avoided, can lead to best use of SOM models to support policy initiatives and sustainable land management solutions.

Plant water availability is a key factor that determines maize yield response to excess heat. Lack of available data has limited researchers' ability to estimate this relationship at regional and global scales. Using a new soil moisture data set developed by running a crop growth simulator over historical data we demonstrate how current estimates of maize yield sensitivity to high temperature are misleading. We develop an empirical model relating observed yields to climate variables and soil moisture in a high maize production region in the United States to develop bounds on yield sensitivity to high temperatures. For the portion of the region with a relatively long growing season, yield reduction per °C is 10% for high water availability and 32.5% for low water availability. Where the growing season is shorter, yield reduction per °C is 6% for high water availability and 27% for low water availability. These results indicate the importance of using both water availability and temperature to model crop yield response to explain future climate change on crop yields.

Agricultural production across eastern Australia and New Zealand is highly vulnerable to drought, but there is a dearth of observational drought information prior to CE 1850. Using a comprehensive network of 176 drought-sensitive tree-ring chronologies and one coral series, we report the first Southern Hemisphere gridded drought atlas extending back to CE 1500. The austral summer (December–February) Palmer drought sensitivity index reconstruction accurately reproduces historically documented drought events associated with the first European settlement of Australia in CE 1788, and the leading principal component explains over 50% of the underlying variance. This leading mode of variability is strongly related to the Interdecadal Pacific Oscillation tripole index (IPO), with a strong and robust antiphase correlation between (1) eastern Australia and the New Zealand North Island and (2) the South Island. Reported positive, negative, and neutral phases of the IPO are consistently reconstructed by the drought atlas although the relationship since CE 1976 appears to have weakened.

The Russian heatwave in 2010 killed tens of thousands of people, and was by far the worst event in Europe since at least 1950, according to recent studies and a novel universal heatwave index capturing both the duration and magnitude of heatwaves. Here, by taking an improved version of this index, namely the heat wave magnitude index daily, we rank the top ten European heatwaves that occurred in the period 1950–2014, and show the spatial distribution of the magnitude of the most recent heatwave in summer 2015. We demonstrate that all these events had a strong impact reported in historical newspapers. We further reveal that the 1972 heatwave in Finland had a comparable spatial extent and magnitude as the European heatwave of 2003, considered the second strongest heatwave of the observational era. In the next two decades (2021–2040), regional climate projections suggest that Europe experiences an enhanced probability for heatwaves comparable to or greater than the magnitude, extent and duration of the Russian heatwave in 2010. We demonstrate that the probability of experiencing a major European heatwave in the coming decades is higher in RCP8.5 than RCP4.5 even though global mean temperature projections do not differ substantially. This calls for a proactive vulnerability assessment in Europe in support of formulating heatwave adaptation strategies to reduce the adverse impacts of heatwaves.

Land use change in South America, mainly deforestation, is a large source of anthropogenic CO₂ emissions. Identifying and addressing the causes or drivers of anthropogenic forest change is considered crucial for global climate change mitigation. Few countries however, monitor deforestation drivers in a systematic manner. National-level quantitative spatially explicit information on drivers is often lacking. This study quantifies proximate drivers of deforestation and related carbon losses in South America based on remote sensing time series in a systematic, spatially explicit manner. Deforestation areas were derived from the 2010 global remote sensing survey of the Food and Agricultural Organisation Forest Resource Assessment. To assess proximate drivers, land use following deforestation was assigned by visual interpretation of high-resolution satellite imagery. To estimate gross carbon losses from deforestation, default Tier 1 biomass levels per country and eco-zone were used. Pasture was the dominant driver of forest area (71.2%) and related carbon loss (71.6%) in South America, followed by commercial cropland (14% and 12.1% respectively). Hotspots of deforestation due to pasture occurred in Northern Argentina, Western Paraguay, and along the arc of deforestation in Brazil where they gradually moved into higher biomass forests causing additional carbon losses. Deforestation driven by commercial cropland increased in time, with hotspots occurring in Brazil (Mato Grosso State), Northern Argentina, Eastern Paraguay and Central Bolivia. Infrastructure, such as urban expansion and roads, contributed little as proximate drivers of forest area loss (1.7%). Our findings contribute to the understanding of drivers of deforestation and related carbon losses in South America, and are comparable at the national, regional and continental level. In addition, they support the development of national REDD+ interventions and forest monitoring systems, and provide valuable input for statistical analysis and modelling of underlying drivers of deforestation.

Interbasin water transfers are globally important water management strategies, yet little is known about their role in the hydrologic cycle at regional and continental scales. Specifically, there is a dearth of centralized information on transfer locations and characteristics, and few analyses place transfers into a relevant hydrological context. We assessed hydrological characteristics of interbasin transfers (IBTs) in the conterminous US using a nationwide inventory of transfers together with historical climate data and hydrological modeling. Supplying and receiving drainage basins share similar hydroclimatological conditions, suggesting that climatological drivers of water shortages in receiving basins likely have similar effects on supplying basins. This result calls into question the effectiveness of transfers as a strategy to mitigate climate-driven water shortages, as the water shortage may be displaced but not resolved. We also identified hydrologically advantageous and disadvantageous IBTs by comparing the water balances of supplying and receiving basins. Transfer magnitudes did not vary between the two categories, confirming that factors driving individual IBTs, such as patterns of human water demand or engineering constraints, also influence the continental-scale distribution of transfers. Some IBTs impact streamflow for hundreds of kilometers downstream. Transfer magnitude, hydroclimate and organization of downstream river networks mediate downstream impacts, and these impacts have the potential to expand downstream nonlinearly during years of drought. This work sheds new light on IBTs and emphasizes the need for updated inventories and analyses that place IBTs in an appropriate hydrological context.

Microplastic debris floating at the ocean surface can harm marine life. Understanding the severity of this harm requires knowledge of plastic abundance and distributions. Dozens of expeditions measuring microplastics have been carried out since the 1970s, but they have primarily focused on the North Atlantic and North Pacific accumulation zones, with much sparser coverage elsewhere. Here, we use the largest dataset of microplastic measurements assembled to date to assess the confidence we can have in global estimates of microplastic abundance and mass. We use a rigorous statistical framework to standardize a global dataset of plastic marine debris measured using surface-trawling plankton nets and coupled this with three different ocean circulation models to spatially interpolate the observations. Our estimates show that the accumulated number of microplastic particles in 2014 ranges from 15 to 51 trillion particles, weighing between 93 and 236 thousand metric tons, which is only approximately 1% of global plastic waste estimated to enter the ocean in the year 2010. These estimates are larger than previous global estimates, but vary widely because the scarcity of data in most of the world ocean, differences in model formulations, and fundamental knowledge gaps in the sources, transformations and fates of microplastics in the ocean.

Shore pine, which is a subspecies of lodgepole pine, was a widespread and dominant tree species in Southeast Alaska during the early Holocene. At present, the distribution of shore pine in Alaska is restricted to coastal bogs and fens, likely by competition with Sitka spruce and Western hemlock. Monitoring of permanent plots as part of the United States Forest Service Forest Inventory and Analysis program identified a recent loss of shore pine biomass in Southeast Alaska. The apparent loss of shore pine is concerning, because its presence adds a vertical dimension to coastal wetlands, which are the richest plant communities of the coastal temperate rainforest in Alaska. In this study, we examined the shore pine tree-ring record from a newly established plot network throughout Southeast Alaska and explored climate-growth relationships. We found a steep decline in shore pine growth from the early 1960s to the present. Random Forest regression revealed a strong correlation between the decline in shore pine growth and the rise in growing season diurnal minimum air temperature. Warm summer nights, cool daytime temperatures and a reduced diurnal temperature range are associated with greater cloud cover in Southeast Alaska. This suite of conditions could lead to unfavorable tree carbon budgets (reduced daytime photosynthesis and greater nighttime respiration) and/or favor infection by foliar pathogens, such as Dothistroma needle blight, which has recently caused widespread tree mortality on lodgepole pine plantations in British Columbia. Further field study that includes experimental manipulation (e.g., fungicide application) will be necessary to identify the proximal cause(s) of the growth decline. In the meantime, we anticipate continuation of the shore pine growth decline in Southeast Alaska.

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 CO₂ 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.

Lay judgments of environmental risks are central to both immediate decisions (e.g., taking shelter from a storm) and long-term ones (e.g., building in locations subject to storm surges). Using methods from quantitative psychology, we provide a general approach to studying lay perceptions of environmental risks. As a first application of these methods, we investigate a setting where lay decisions have not taken full advantage of advances in natural science understanding: tornado forecasts in the US and Canada. Because official forecasts are imperfect, members of the public must often evaluate the risks on their own, by checking environmental cues (such as cloud formations) before deciding whether to take protective action. We study lay perceptions of cloud formations, demonstrating an approach that could be applied to other environmental judgments. We use signal detection theory to analyse how well people can distinguish tornadic from non-tornadic clouds, and multidimensional scaling to determine how people make these judgments. We find that participants (N = 400 recruited from Amazon Mechanical Turk) have heuristics that generally serve them well, helping participants to separate tornadic from non-tornadic clouds, but which also lead them to misjudge the tornado risk of certain cloud types. The signal detection task revealed confusion regarding shelf clouds, mammatus clouds, and clouds with upper- and mid-level tornadic features, which the multidimensional scaling task suggested was the result of participants focusing on the darkness of the weather scene and the ease of discerning its features. We recommend procedures for training (e.g., for storm spotters) and communications (e.g., tornado warnings) that will reduce systematic misclassifications of tornadicity arising from observers' reliance on otherwise useful heuristics.

We estimate the total land water storage (LWS) change between 2003 and 2013 using a global water mass budget approach. Hereby we compare the ocean mass change (estimated from GRACE space gravimetry on the one hand, and from the satellite altimetry-based global mean sea level corrected for steric effects on the other hand) to the sum of the main water mass components of the climate system: glaciers, Greenland and Antarctica ice sheets, atmospheric water and LWS (the latter being the unknown quantity to be estimated). For glaciers and ice sheets, we use published estimates of ice mass trends based on various types of observations covering different time spans between 2003 and 2013. From the mass budget equation, we derive a net LWS trend over the study period. The mean trend amounts to +0.30 ± 0.18 mm yr⁻¹ in sea level equivalent. This corresponds to a net decrease of −108 ± 64 km³ yr⁻¹ in LWS over the 2003–2013 decade. We also estimate the rate of change in LWS and find no significant acceleration over the study period. The computed mean global LWS trend over the study period is shown to be explained mainly by direct anthropogenic effects on land hydrology, i.e. the net effect of groundwater depletion and impoundment of water in man-made reservoirs, and to a lesser extent the effect of naturally-forced land hydrology variability. Our results compare well with independent estimates of human-induced changes in global land hydrology.

Global warming is likely to exacerbate future fluvial floods in the world's mega-delta regions due to both changing climate and rising sea levels. However, the effects of sea level rise (SLR) on fluvial floods in such regions have not been taken into account in current global assessments of future flood risk, due to the difficulties in modeling channel bifurcation and the backwater effect. We used a state-of-the-art global river routing model to demonstrate how these complexities contribute to future flood hazard associated with changing climate and SLR in the world's largest mega-delta region, the Ganges-Brahmaputra-Meghna Delta. The model demonstrated that flood water in the main channels flows into tributaries through bifurcation channels, which resulted in an increase in inundation depth in deltaic regions. We found that there were large areas that experienced an increase in inundation depth and period not directly from the SLR itself but from the backwater effect of SLR, and the effect propagated upstream to locations far from the river mouth. Projections under future climate scenarios as well as SLR indicated that exposure to fluvial floods will increase in the last part of the 21st century, and both SLR and channel bifurcation make meaningful contributions.

Roof surface materials, such as green and white roofs, have attracted attention in their role in urban heat mitigation, and various studies have assessed the cooling performance of roof surface materials during hot and sunny summer seasons. However, summers in the East Asian monsoon climate region are characterized by significant fluctuations in weather events, such as dry periods, heatwaves, and rainy and cloudy days. This study investigated the efficacy of different roof surface materials for heat mitigation, considering the temperatures both at and beneath the surface of the roof covering materials during a summer monsoon in Seoul, Korea. We performed continuous observations of temperature at and beneath the surface of the roof covering materials, and manual observation of albedo and the normalized difference vegetation index for a white roof, two green roofs (grass (Poa pratensis) and sedum (Sedum sarmentosum)), and a reference surface. Overall, the surface temperature of the white roof was significantly lower than that of the grass and sedum roofs (1.1 °C and 1.3 °C), whereas the temperature beneath the surface of the white roof did not differ significantly from that of the grass and sedum roofs during the summer. The degree of cloudiness significantly modified the surface temperature of the white roof compared with that of the grass and sedum roofs, which depended on plant metabolisms. It was difficult for the grass to maintain its cooling ability without adequate watering management. After considering the cooling performance and maintenance efforts for different environmental conditions, we concluded that white roof performed better in urban heat mitigation than grass and sedum during the East Asian summer monsoon. Our findings will be useful in urban heat mitigation in the region.

Drought is a natural hazard triggered by a lack of precipitation that can last for several months or years. Droughts can affect a wide range of socio-economic sectors while the related direct and indirect impacts are often difficult to quantify. In this context, drought damage refers to the total or partial destruction of physical assets in the affected area. The main constraint in constructing a robust relationship between the severity of drought events and related damages is the lack of sufficient quantitative impact data. In this paper we propose the use of power-law damage functions to assess the relationship between drought severity and related damages in two economic sectors, namely cereal crop production and hydropower generation, across 21 European countries. The different shapes of the resulting damage functions can be explained by the specific drought vulnerability or adaptive capacity of each sector and country. Due to the scarcity of impact data linked to extreme climate events a bootstrap resampling was performed to assess the potential uncertainties associated with the sample size. This approach helps communicating potential drought impacts and related uncertainties to end users and policy makers in support to the development of drought management plans and long-term adaptation measures.

The challenge of estimating the potential impacts of climate change has led to an increasing use of dynamical downscaling to produce fine spatial-scale climate projections for impact assessments. In this work, we analyze if and to what extent the bias in the simulated crop yield can be reduced by using the Weather Research and Forecasting (WRF) regional climate model to downscale ERA-Interim (European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis) rainfall and radiation data. Then, we evaluate the uncertainties resulting from both the choice of the physical parameterizations of the WRF model and its internal variability. Impact assessments were performed at two sites in Sub-Saharan Africa and by using two crop models to simulate Niger pearl millet and Benin maize yields. We find that the use of the WRF model to downscale ERA-Interim climate data generally reduces the bias in the simulated crop yield, yet this reduction in bias strongly depends on the choices in the model setup. Among the physical parameterizations considered, we show that the choice of the land surface model (LSM) is of primary importance. When there is no coupling with a LSM, or when the LSM is too simplistic, the simulated precipitation and then the simulated yield are null, or respectively very low; therefore, coupling with a LSM is necessary. The convective scheme is the second most influential scheme for yield simulation, followed by the shortwave radiation scheme. The uncertainties related to the internal variability of the WRF model are also significant and reach up to 30% of the simulated yields. These results suggest that regional models need to be used more carefully in order to improve the reliability of impact assessments.

Dependence upon groundwater to meet rising agricultural and domestic water needs is expected to increase substantially across the tropics where, by 2050, over half of the world's population is projected to live. Rare, long-term groundwater-level records in the tropics indicate that groundwater recharge occurs disproportionately from heavy rainfalls exceeding a threshold. The ubiquity of this bias in tropical groundwater recharge to intensive precipitation is, however, unknown. By relating available long-term records of stable-isotope ratios of O and H in tropical precipitation (15 sites) to those of local groundwater, we reveal that groundwater recharge in the tropics is near-uniformly (14/15 sites) biased to intensive monthly rainfall, commonly exceeding the ∼70th intensity decile. Our results suggest that the intensification of precipitation brought about by global warming favours groundwater replenishment in the tropics. Nevertheless, the processes that transmit intensive rainfall to groundwater systems and enhance the resilience of tropical groundwater storage in a warming world, remain unclear.

Palustrine wetlands (PWs) include all bogs, fens, swamps and marshes that are non-saline and which are not lakes or rivers. They therefore form a highly important group of wetlands which hold large carbon stocks. If these wetlands are not protected properly they could become a net carbon source in the future. Compilation of spatially explicit wetland databases, national inventory data and in situ measurement of soil organic carbon (SOC) could be useful to better quantify SOC and formulate long-term strategies for mitigating global climate change. In this study, a synergistic mapping approach was used to create a hybrid map for PWs for China and to estimate their SOC content. Total SOC storage in PWs was estimated to be 4.3 ± 1.4 Pg C, with a SOC density of 31.17 (±10.55) kg C m⁻² in the upper 1 m of the soil layer. This carbon stock is concentrated in Northeast China (49%) and the Qinghai–Tibet Plateau (41%). Given the large pool of carbon stored in PWs compared to other soil types, we suggest that urgent monitoring programmes on SOC should be established in regions with very few datasets, but where PWs appear to be common such as the Tibet region and Northwest China.

Carsharing exemplifies a growing trend towards service provision displacing ownership of capital goods. We developed a model to quantify the impact of carsharing on greenhouse gas (GHG) emissions. The study took into account different types of households and their trip characteristics. The analysis considers five factors by which carsharing can impact GHG emissions: transportation mode change, fleet vintage, vehicle optimization, more efficient drive trains within each vehicle type, and trip aggregation. Access to carsharing has already been shown to lead some users to relinquish ownership of their personal vehicle. We find that even without a reduction in vehicle-kilometers traveled the change in characteristics of the vehicles used in carsharing fleets can reduce GHGs by more than 30%. Shifting some trips to public transit provides a further 10%–20% reduction in GHGs.

Bulk chemicals production from biomass may compete with biofuels for low-cost and sustainable biomass sources. Understanding how alternative uses of biomass compare in terms of financial and environmental parameters is therefore necessary to help ensure that efficient uses of resources are encouraged by policy and undertaken by industry. In this paper, we compare the environmental and financial performance of using ethanol as a feedstock for bioethylene production or as a transport fuel in the US life cycle-based models are developed to isolate the relative impacts of these two ethanol uses and generate results that are applicable irrespective of ethanol production pathway. Ethanol use as a feedstock for bioethylene production or as a transport fuel leads to comparable greenhouse gas (GHG) emissions and fossil energy consumption reductions relative to their counterparts produced from fossil sources. By displacing gasoline use in vehicles, use of ethanol as a transport fuel is six times more effective in reducing petroleum energy use on a life cycle basis. In contrast, bioethylene predominately avoids consumption of natural gas. Considering 2013 US ethanol and ethylene market prices, our analysis shows that bioethylene is financially viable only if significant price premiums are realized over conventional ethylene, from 35% to 65% depending on the scale of bioethylene production considered (80 000 t yr⁻¹ to 240 000 t yr⁻¹). Ethanol use as a transportation fuel is therefore the preferred pathway considering financial, GHG emissions, and petroleum energy use metrics, although bioethylene production could have strategic value if demand-side limitations of ethanol transport fuel markets are reached.

Brazil plans to meet the majority of its growing electricity demand with new hydropower plants located in the Amazon basin. However, large hydropower plants located in tropical forested regions may lead to significant carbon dioxide and methane emission. Currently, no predictive models exist to estimate the greenhouse gas emissions before the reservoir is built. This paper presents two different approaches to investigate the future carbon balance of eighteen new reservoirs in the Amazon. The first approach is based on a degradation model of flooded carbon stock, while the second approach is based on flux data measured in Amazonian rivers and reservoirs. The models rely on a Monte Carlo simulation framework to represent the balance of the greenhouse gases into the atmosphere that results when land and river are converted into a reservoir. Further, we investigate the role of the residence time/stratification in the carbon emissions estimate. Our results imply that two factors contribute to reducing overall emissions from these reservoirs: high energy densities reservoirs, i.e., the ratio between the installed capacity and flooded area, and vegetation clearing. While the models' uncertainties are high, we show that a robust treatment of uncertainty can effectively indicate whether a reservoir in the Amazon will result in larger greenhouse gas emissions when compared to other electricity sources.

Northwestern Siberia has been undergoing a range of land cover and land use changes associated with climate change, animal husbandry and development of mineral resources, particularly oil and gas. The changes caused by climate and oil/gas development Southeast of the city of Nadym were investigated using multi-temporal and multi-spatial remotely sensed images. Comparison between high spatial resolution imagery acquired in 1968 and 2006 indicates that 8.9% of the study area experienced an increase in vegetation cover (e.g. establishment of new saplings, extent of vegetated cover) in response to climate warming while 10.8% of the area showed a decrease in vegetation cover due to oil and gas development and logging activities. Waterlogging along linear structures and vehicle tracks was found near the oil and gas development site, while in natural landscapes the drying of thermokarst lakes is evident due to warming caused permafrost degradation. A Landsat time series dataset was used to document the spatial and temporal dynamics of these ecosystems in response to climate change and disturbances. The impacts of land use on surface vegetation, radiative, and hydrological properties were evaluated using Landsat image-derived biophysical indices. The spatial and temporal analyses suggest that the direct impacts associated with infrastructure development were mostly within 100 m distance from the disturbance source. While these impacts are rather localized they persist for decades despite partial recovery of vegetation after the initial disturbance and can have significant implications for changes in permafrost dynamics and surface energy budgets at landscape and regional scales.

The effects of the tropical Pacific El Niño Southern Oscillation (ENSO) phenomenon are communicated to the rest of the globe via atmospheric teleconnections. Traditionally, ENSO teleconnections have been viewed as tropospheric phenomena, propagating to higher latitudes as Rossby waves. Recent studies, however, suggest an influence of the stratosphere on extra-tropical ENSO teleconnections. The stratosphere is highly variable: in the tropics, the primary mode of variability is the quasi-biennial oscillation (QBO), and in the extra-tropics sudden stratospheric warmings (SSWs) regularly perturb the mean state. Here, we conduct a 10-member ensemble of simulations with a stratosphere-resolving atmospheric general circulation model forced with the observed evolution of sea surface temperatures during 1952–2001 to examine the effects of the QBO and SSWs on the zonal-mean circulation and temperature response to El Niño, with a focus on the northern extra-tropics during winter. We find that SSWs have a larger impact than the QBO on the composite El Niño responses. During El Niño winters with SSWs, the polar stratosphere shows positive temperature anomalies that propagate downward to the surface where they are associated with increased sea-level pressure over the Arctic. During El Niño winters without SSWs, the stratosphere and upper troposphere show negative temperature anomalies but these do not reach the surface. The QBO modulates the El Niño teleconnection primarily in winters without SSWs: the negative temperature anomalies in the polar stratosphere and upper troposphere are twice as large during QBO West compared to QBO East years. In addition, El Niño winters that coincide with the QBO West phase show stronger positive sea-level pressure anomalies over the eastern Atlantic and Northern Europe than those in the QBO East phase. The results imply that the stratosphere imparts considerable variability to ENSO teleconnections.

Unmitigated greenhouse gas emissions may increase global mean sea-level by about 1 meter during this century. Such elevation of the mean sea-level enhances the risk of flooding of coastal areas. We compute the power capacity that is currently out-of-reach of a 100-year coastal flooding but will be exposed to such a flood by the end of the century for different US states, if no adaptation measures are taken. The additional exposed capacity varies strongly among states. For Delaware it is 80% of the mean generated power load. For New York this number is 63% and for Florida 43%. The capacity that needs additional protection compared to today increases by more than 250% for Texas, 90% for Florida and 70% for New York. Current development in power plant building points towards a reduced future exposure to sea-level rise: proposed and planned power plants are less exposed than those which are currently operating. However, power plants that have been retired or canceled were less exposed than those operating at present. If sea-level rise is properly accounted for in future planning, an adaptation to sea-level rise may be costly but possible.

Temperature variability in the Southwest US is investigated using skew-normal probability distribution functions (SN PDFs) fitted to observed wintertime daily maximum temperature records. These PDFs vary significantly between years, with important geographical differences in the relationship between the central tendency and tails, revealing differing linkages between weather and climate. The warmest and coldest extremes do not necessarily follow the distribution center. In some regions one tail of the distribution shows more variability than does the other. For example, in California the cold tail is more variable while the warm tail remains relatively stable, so warm years are associated with fewer cold extremes but not necessarily more warm extremes. The opposite relationship is seen in the Great Plains. Changes in temperature PDFs are conditioned by different phases of El Niño-La Niña (ENSO) and the Pacific decadal oscillation (PDO). In the Southern Great Plains, La Niña and/or negative PDO are associated with generally warmer conditions. However, in terms of extremes, while the warm tails become thicker and longer, the cool tails are not impacted—extremely warm days become more frequent but extremely cool days are not less frequent. In contrast, in coastal California, La Niña or negative PDO bring generally cooler conditions with more/stronger cold extremes but the warm extreme probability is not significantly affected. These results could have implications for global warming. If a rigid shift of the whole range occurs, then warm years are not necessarily a good analogue for a warmer climate. If global warming instead brings regional changes more aligned with a preferred state of dominant climate variability modes, then we may see asymmetric changes in the tails of local temperature PDFs.

We use GRACE-derived terrestrial water storage (TWS) and ERA-interim air temperature, as proxy for available water and temperature constraints on vegetation productivity, inferred from MODIS satellite normalized difference vegetation index (NDVI), in Northern Eurasia during 2002–2011. We investigate how changes in TWS affect the correlation between NDVI and temperature during the non-frozen season. We find that vegetation growth exhibits significant spatial and temporal variability associated with varying trend in TWS and temperature. The largest NDVI gains occur over boreal forests associated with warming and wetting. The largest NDVI losses occur over grasslands in the Southwestern Ob associated with regional drying and cooling, with dominant constraint from TWS. Over grasslands and temperate forests in the Southeast Ob and South Yenisei, wetting and cooling lead to a dominant temperature constraint due to the relaxation of TWS constraints. Overall, we find significant monthly correlation of NDVI with TWS and temperature over 35% and 50% of the domain, respectively. These results indicate that water availability (TWS) plays a major role in modulating Eurasia vegetation response to temperature changes.

Assessing the impacts of land use and land cover change (LUCC) on regional climate is essential for understanding land–atmosphere interactions and for designing climate adaptation and mitigation strategies. Using the weather research and forecasting (WRF) model, we examined how different land use and land cover patterns affect regional climate in the agro-pastoral transitional zone of North China, whose environmental and socioeconomic conditions are sensitive to climate change. We parameterized WRF using land use and land cover maps corresponding to 2001 and 2010 conditions, which differ in the representation of four land surface biophysical parameters: vegetation fraction, leaf area index (LAI), albedo, and emissivity. From 2001 to 2010, vegetation fraction and LAI increased in summer, emissivity increased and albedo decreased in winter. Our WRF simulations show that differences in land use and land cover patterns led to widespread reduction in summer temperature with local cooling on the order of 1 °C, and extensive increase in winter temperature with local warming exceeding 0.8 °C. By contrast, simulations using the default landscape representation, provided by WRF itself, show only minor and random changes in temperature. Model evaluation further reveals that our simulations with appropriate land surface properties improve the performance of the WRF model. Our findings demonstrate that LUCC in Northern China has altered the regional climate over the past decade. The magnitude and spatial patterns of temperature changes quantified by our simulations provide useful information for understanding the impacts of LUCC on climate and for developing mitigation and adaptation strategies in arid and semiarid regions.

Societies and economies are challenged by variable water supplies. Water storage infrastructure, on a range of scales, can help to mitigate hydrological variability. This study uses a water balance model to investigate how storage capacity can improve water security in the world's 403 most important river basins, by substituting water from wet months to dry months. We construct a new water balance model for 676 'basin-country units' (BCUs), which simulates runoff, water use (from surface and groundwater), evaporation and trans-boundary discharges. When hydrological variability and net withdrawals are taken into account, along with existing storage capacity, we find risks of water shortages in the Indian subcontinent, Northern China, Spain, the West of the US, Australia and several basins in Africa. Dividing basins into BCUs enabled assessment of upstream dependency in transboundary rivers. Including Environmental Water Requirements into the model, we find that in many basins in India, Northern China, South Africa, the US West Coast, the East of Brazil, Spain and in the Murray basin in Australia human water demand leads to over-abstraction of water resources important to the ecosystem. Then, a Sequent Peak Analysis is conducted to estimate how much storage would be needed to satisfy human water demand whilst not jeopardizing environmental flows. The results are consistent with the water balance model in that basins in India, Northern China, Western Australia, Spain, the US West Coast and several basins in Africa would need more storage to mitigate water supply variability and to meet water demand.

The international community has set a goal to limit global warming to 2 °C. Limiting global warming to 2 °C is a challenging goal and will entail a dramatic transformation of the global energy system, largely complete by 2040. As part of the work toward this goal, countries have been submitting their Intended Nationally Determined Contributions (INDCs) to the United Nations Framework Convention on Climate Change, indicating their emissions reduction commitments through 2025 or 2030, in advance of the 21st Conference of the Parties (COP21) in Paris in December 2015. In this paper, we use the Global Change Assessment Model (GCAM) to analyze the near versus long-term energy and economic-cost implications of these INDCs. The INDCs imply near-term actions that reduce the level of mitigation needed in the post-2030 period, particularly when compared with an alternative path in which nations are unable to undertake emissions mitigation until after 2030. We find that the latter case could require up to 2300 GW of premature retirements of fossil fuel power plants and up to 2900 GW of additional low-carbon power capacity installations within a five-year period of 2031–2035. INDCs have the effect of reducing premature retirements and new-capacity installations after 2030 by 50% and 34%, respectively. However, if presently announced INDCs were strengthened to achieve greater near-term emissions mitigation, the 2031–2035 transformation could be tempered to require 84% fewer premature retirements of power generation capacity and 56% fewer new-capacity additions. Our results suggest that the INDCs delivered for COP21 in Paris will have important contributions in reducing the challenges of achieving the goal of limiting global warming to 2 °C.

The near proportionality between cumulative CO₂ emissions and change in near surface temperature can be used to define a carbon budget: a finite quantity of carbon that can be burned associated with a chosen 'safe' temperature change threshold. Here we evaluate the sensitivity of this carbon budget to permafrost carbon dynamics and changes in non-CO₂ forcings. The carbon budget for 2.0 ${}^{\circ }{\rm{C}}$ of warming is reduced from 1320 Pg C when considering only forcing from CO₂ to 810 Pg C when considering permafrost carbon feedbacks as well as other anthropogenic contributions to climate change. We also examined net carbon budgets following an overshoot of and return to a warming target. That is, the net cumulative CO₂ emissions at the point in time a warming target is restored following artificial removal of CO₂ from the atmosphere to cool the climate back to a chosen temperature target. These overshoot net carbon budgets are consistently smaller than the conventional carbon budgets. Overall carbon budgets persist as a robust and simple conceptual framework to relate the principle cause of climate change to the impacts of climate change.

Climate change is projected to negatively impact biophysical agricultural productivity in much of the world. Actions taken to reduce greenhouse gas emissions and mitigate future climate changes, are thus of central importance for agricultural production. Climate impacts are, however, not unidirectional; some crops in some regions (primarily higher latitudes) are projected to benefit, particularly if increased atmospheric carbon dioxide is assumed to strongly increase crop productivity at large spatial and temporal scales. Climate mitigation measures that are implemented by reducing atmospheric carbon dioxide concentrations lead to reductions both in the strength of climate change and in the benefits of carbon dioxide fertilization. Consequently, analysis of the effects of climate mitigation on agricultural productivity must address not only regions for which mitigation is likely to reduce or even reverse climate damages. There are also regions that are likely to see increased crop yields due to climate change, which may lose these added potentials under mitigation action. Comparing data from the most comprehensive archive of crop yield projections publicly available, we find that climate mitigation leads to overall benefits from avoided damages at the global scale and especially in many regions that are already at risk of food insecurity today. Ignoring controversial carbon dioxide fertilization effects on crop productivity, we find that for the median projection aggressive mitigation could eliminate ∼81% of the negative impacts of climate change on biophysical agricultural productivity globally by the end of the century. In this case, the benefits of mitigation typically extend well into temperate regions, but vary by crop and underlying climate model projections. Should large benefits to crop yields from carbon dioxide fertilization be realized, the effects of mitigation become much more mixed, though still positive globally and beneficial in many food insecure countries.

Spatial variability and temporal trends of the shallow ground thermal regime and permafrost active-layer thickness (ALT) were estimated over 1963–2013 using daily soil temperature data available from stations of the Russian Hydrometeorological Service. Correlation analysis was used to evaluate the role of changing climatic conditions on the ground thermal regime. ALT data collected by the Circumpolar Active Layer Monitoring program in Russia were used to expand the geography of ALT observations over 1999–2013, and to identify 'hot spots' of soil temperature and ALT change. Results indicate that a substantially higher rate of change in the thermal regime of permafrost-affected soils prevailed during 1999–2013, relative to the last fifty years. Results indicate that the thermal regime of the upper permafrost in western Russia is strongly associated with air temperature, with much weaker relationships in central and eastern Russia. The thermal regime of permafrost-affected soils shows stronger dependence on climatic conditions over the last fifteen years relative to the historical 50-year period. Geostatistical analysis revealed that the cities of Norilsk and Susuman are hot spots of permafrost degradation. Of six settlements selected for detailed analysis in various parts of the permafrost regions, all but one (Chukotka), show substantial changes in the shallow ground thermal regime. Northern locations in the continuous permafrost region show thickening of the active layer, while those farther south experienced development of residual thaw layers above the permafrost and decreases in the duration of the freezing period.

The aim of this work is an analysis of the causes of spruce (Picea abies L.) decline and mortality in Belarus. The analysis was based on forest inventory and Landsat satellite (land cover classification, climate variables (air temperature, precipitation, evaporation, vapor pressure deficit, SPEI drought index)), and GRACE-derived soil moisture estimation (equivalent of water thickness anomalies, EWTA). We found a difference in spatial patterns between dead stands and all stands (i.e., before mortality). Dead stands were located preferentially on relief features with higher water stress risk (i.e., higher elevations, steeper slopes, south and southwestern exposure). Spruce mortality followed a series of repeated droughts between 1990 and 2010. Mortality was negatively correlated with air humidity (r = –0.52), and precipitation (r = –0.57), and positively correlated with the prior year vapor pressure deficit (r = 0.47), and drought increase (r = 0.57). Mortality increased with the increase in occurrence of spring frosts (r = 0.5), and decreased with an increase in winter cloud cover (r = –0.37). Spruce mortality was negatively correlated with snow water accumulation (r = –0.81) and previous year anomalies in water soil content (r = –0.8). Weakened by water stress, spruce stands were attacked by pests and phytopathogens. Overall, spruce mortality in Belarussian forests was caused by drought episodes and drought increase in synergy with pest and phytopathogen attacks. Vast Picea abies mortality in Belarus and adjacent areas of Russia and Eastern Europe is a result of low adaptation of that species to increased drought. This indicates the necessity of spruce replacement by drought-tolerant indigenous (e.g., Pinus sylvestris, Querqus robur) or introduced (e.g., Larix sp. or Pseudotsuga menzieslii) species to obtain sustainable forest growth management.

The dynamic global vegetation model (DGVM) SEVER has been regionally adapted using a remote sensing data-derived land cover map in order to improve the reconstruction conformity of the distribution of vegetation functional types over Russia. The SEVER model was modified to address noticeable divergences between modelling results and the land cover map. The model modification included a light competition method elaboration and the introduction of a tundra class into the model. The rigorous optimisation of key model parameters was performed using a two-step procedure. First, an approximate global optimum was found using the efficient global optimisation (EGO) algorithm, and afterwards a local search in the vicinity of the approximate optimum was performed using the quasi-Newton algorithm BFGS. The regionally adapted model shows a significant improvement of the vegetation distribution reconstruction over Russia with better matching with the satellite-derived land cover map, which was confirmed by both a visual comparison and a formal conformity criterion.

Multi-reservoir system planners should consider how new dams impact downstream reservoirs and the potential contribution of each component to coordinated management. We propose an optimized multi-criteria screening approach to identify best performing designs, i.e., the selection, size and operating rules of new reservoirs within multi-reservoir systems. Reservoir release operating rules and storage sizes are optimized concurrently for each separate infrastructure design under consideration. Outputs reveal system trade-offs using multi-dimensional scatter plots where each point represents an approximately Pareto-optimal design. The method is applied to proposed Blue Nile River reservoirs in Ethiopia, where trade-offs between total and firm energy output, aggregate storage and downstream irrigation and energy provision for the best performing designs are evaluated. This proof-of concept study shows that recommended Blue Nile system designs would depend on whether monthly firm energy or annual energy is prioritized. 39 TWh/yr of energy potential is available from the proposed Blue Nile reservoirs. The results show that depending on the amount of energy deemed sufficient, the current maximum capacities of the planned reservoirs could be larger than they need to be. The method can also be used to inform which of the proposed reservoir type and their storage sizes would allow for the highest downstream benefits to Sudan in different objectives of upstream operating objectives (i.e., operated to maximize either average annual energy or firm energy). The proposed approach identifies the most promising system designs, reveals how they imply different trade-offs between metrics of system performance, and helps system planners asses the sensitivity of overall performance to the design parameters of component reservoirs.

Aim: estimation of larch (Larix gmelinii) growth response to current climate changes. Location: permafrost area within the northern part of Central Siberia (∼65.8°N, 98.5°E). Method: analysis of dendrochronological data, climate variables, drought index SPEI, GPP (gross primary production) and EVI vegetation index (both Aqua/MODIS satellite derived), and soil water content anomalies (GRACE satellite measurements of equivalent water thickness anomalies, EWTA). Results: larch tree ring width (TRW) correlated with previous year August precipitation (r = 0.63), snow accumulation (r = 0.61), soil water anomalies (r = 0.79), early summer temperatures and water vapor pressure (r = 0.73 and r = 0.69, respectively), May and June drought index (r = 0.68–0.82). There are significant positive trends of TRW since late 1980 s and GPP since the year 2000. Mean TRW increased by about 50%, which is similar to post-Little Ice Age warming. TRW correlated with GPP and EVI of larch stands (r = 0.68–0.69). Main conclusions: within the permafrost zone of central Siberia larch TRW growth is limited by early summer temperatures, available water from snowmelt, water accumulated within soil in the previous year, and permafrost thaw water. Water stress is one of the limiting factors of larch growth. Larch TRW growth and GPP increased during recent decades.

International conservation donors have spent at least $3.4 billion to protect biodiversity and stem tropical deforestation in Africa since the early 1990s. Despite more than two decades of experience, however, there is little research on the effect of this aid at a region-wide scale. Numerous case studies exist, but show mixed results. Existing research is usually based on community perception or focused on short-term donor objectives rather than specific conservation outcomes, like deforestation rates. Thus, the impact of billions of dollars of conservation aid on deforestation rates remains an open question. This article uses an original dataset to analyze the effect of international conservation aid on deforestation rates in 42 African countries between 2000 and 2013. We first describe patterns of conservation aid across the continent and then assess its impact (with one to five-year lags), controlling for other factors that may also affect deforestation, including rural population, protected areas (PAs), governance, and other economic and commodity production variables. We find that conservation aid is associated with higher rates of forest loss after one- or two-year lags. A similar result holds for PA extent, suggesting possible displacement of deforestation from PAs. However, governance quality in high forest cover countries moderates these effects such that deforestation rates are reduced. Rural population is the most consistent factor associated with forest loss, confirming previous studies of this driver. Our results suggest that in heavily forested countries, development projects designed to support conservation work initially in conditions of good governance, but that conservation aid alone is insufficient to mitigate larger deforestation drivers.

A considerable number of quantitative analyses have been conducted in the past several decades that demonstrate the existence of racial and socioeconomic disparities in the distribution of a wide variety of environmental hazards. The vast majority of these have been cross-sectional, snapshot studies employing data on hazardous facilities and population characteristics at only one point in time. Although some limited hypotheses can be tested with cross-sectional data, fully understanding how present-day disparities come about requires longitudinal analyses that examine the demographic characteristics of sites at the time of facility siting and track demographic changes after siting. Relatively few such studies exist and those that do exist have often led to confusing and contradictory findings. In this paper we review the theoretical arguments, methods, findings, and conclusions drawn from existing longitudinal environmental justice studies. Our goal is to make sense of this literature and to identify the direction future research should take in order to resolve confusion and arrive at a clearer understanding of the processes and contributory factors by which present-day racial and socioeconomic disparities in the distribution of environmental hazards have come about. Such understandings also serve as an important step in identifying appropriate and effective societal responses to ameliorate environmental disparities.

Production of commercial agricultural commodities for domestic and foreign markets is increasingly driving land clearing in tropical regions, creating links and feedback effects between geographically separated consumption and production locations. Such teleconnections are commonly studied through calculating consumption footprints and quantifying environmental impacts embodied in trade flows, e.g., virtual water and land, biomass, or greenhouse gas emissions. The extent to which land-use change (LUC) and associated carbon emissions are embodied in the production and export of agricultural commodities has been less studied. Here we quantify tropical deforestation area and carbon emissions from LUC induced by the production and the export of four commodities (beef, soybeans, palm oil, and wood products) in seven countries with high deforestation rates (Argentina, Bolivia, Brazil, Paraguay, Indonesia, Malaysia, and Papua New Guinea). We show that in the period 2000–2011, the production of the four analyzed commodities in our seven case countries was responsible for 40% of total tropical deforestation and resulting carbon losses. Over a third of these impacts was embodied in exports in 2011, up from a fifth in 2000. This trend highlights the growing influence of global markets in deforestation dynamics. Main flows of embodied LUC are Latin American beef and soybean exports to markets in Europe, China, the former Soviet bloc, the Middle East and Northern Africa, whereas embodied emission flows are dominated by Southeast Asian exports of palm oil and wood products to consumers in China, India and the rest of Asia, as well as to the European Union. Our findings illustrate the growing role that global consumers play in tropical LUC trajectories and highlight the need for demand-side policies covering whole supply chains. We also discuss the limitations of such demand-side measures and call for a combination of supply- and demand-side policies to effectively limit tropical deforestation, along with research into the interactions of different types of policy interventions.

Human demand for animal products has risen markedly over the past 50 years with important environmental impacts. Dairy and cattle production have disproportionately contributed to greenhouse gas (GHG) emissions and land use, while crop demands of more intensive systems have increased fertilizer use and competition for available crop calories. At the same time, chicken and pig production has grown more rapidly than for ruminants, indicating a change in the environmental burden per animal calorie (EBC) with time. How EBCs have changed and to what extent resource use efficiency (RUE), the composition of animal production and the trade of feed have played a role in these changes have not been examined to date. We employ a calorie-based perspective, distinguishing animal calorie production between calories produced from feedcrop sources—directly competing with humans for available calories—and those from non-feed sources—plant biomass unavailable for direct human consumption. Combining this information with data on agricultural resource use, we calculate EBCs in terms of land, GHG emissions and nitrogen. We find that EBCs have changed substantially for land (−62%), GHGs (−46%) and nitrogen (+188%). Changes in RUE (e.g., selective breeding, increased grain-feeding) have been the primary contributor to these EBC trends, but shifts in the composition of livestock production were responsible for 12%–41% of the total EBC changes. In addition, the virtual trade of land for feed has more than tripled in the past 25 years with 77% of countries currently relying on virtual land imports to support domestic livestock production. Our findings indicate that important tradeoffs have occurred as a result of livestock intensification, with more efficient land use and emission rates exchanged for greater nitrogen use and increased competition between feed and food. This study provides an integrated evaluation of livestock's impact on food security and the environment.

The food production system is increasingly global and seafood is among the most highly traded commodities. Global trade can improve food security by providing access to a greater variety of foods, increasing wealth, buffering against local supply shocks, and benefit the environment by increasing overall use efficiency for some resources. However, global trade can also expose countries to external supply shocks and degrade the environment by increasing resource demand and loosening feedbacks between consumers and the impacts of food production. As a result, changes in global food trade can have important implications for both food security and the environmental impacts of production. Measurements of globalization and the environmental impacts of food production require data on both total trade and the origin and destination of traded goods (the network structure). While the global trade network of agricultural and livestock products has previously been studied, seafood products have been excluded. This study describes the structure and evolution of the global seafood trade network, including metrics quantifying the globalization of seafood, shifts in bilateral trade flows, changes in centrality and comparisons of seafood to agricultural and industrial trade networks. From 1994 to 2012 the number of countries trading in the network remained relatively constant, while the number of trade partnerships increased by over 65%. Over this same period, the total quantity of seafood traded increased by 58% and the value increased 85% in real terms. These changes signify the increasing globalization of seafood products. Additionally, the trade patterns in the network indicate: increased influence of Thailand and China, strengthened intraregional trade, and increased exports from South America and Asia. In addition to characterizing these network changes, this study identifies data needs in order to connect seafood trade with environmental impacts and food security outcomes.

Earlier research that reports a correlational pattern between climate anomalies and violent conflict routinely refers to drought-induced agricultural shocks and adverse economic spillover effects as a key causal mechanism linking the two phenomena. Comparing half a century of statistics on climate variability, food production, and political violence across Sub-Saharan Africa, this study offers the most precise and theoretically consistent empirical assessment to date of the purported indirect relationship. The analysis reveals a robust link between weather patterns and food production where more rainfall generally is associated with higher yields. However, the second step in the causal model is not supported; agricultural output and violent conflict are only weakly and inconsistently connected, even in the specific contexts where production shocks are believed to have particularly devastating social consequences. Although this null result could, in theory, be fully compatible with recent reports of food price-related riots, it suggests that the wider socioeconomic and political context is much more important than drought and crop failures in explaining violent conflict in contemporary Africa.

Climate has warmed substantially in interior Alaska and several remote sensing studies have documented a decadal-scale decline in the normalized difference vegetation index (NDVI) termed a 'browning trend'. Reduced summer soil moisture due to changing climatic factors such as earlier springs, less snowpack, and summer drought may reduce boreal productivity and NDVI. However, the relative importance of these climatic factors is poorly understood in boreal interior Alaska. In this study, I used the remotely sensed peak summer NDVI as an index of boreal productivity at 250 m pixel size from 2000 to 2014. Maximum summer NDVI was related to last day of spring snow, early spring snow water equivalent (SWE), and a summer moisture index. There was no significant correlation between early spring SWE and peak summer NDVI. There was a significant correlation between the last day of spring snow and peak summer NDVI, but only for a few higher elevation stations. This was likely due to snowmelt occurring later at higher elevations, thus having a greater effect on summer soil moisture relative to lower elevation sites. For most of boreal interior Alaska, summer drought was likely the dominant control on peak summer NDVI and this effect may persist for several years. Peak summer NDVI declined at all 26 stations after the 2004 drought, and the decline persisted for 2 years at all stations. Due to the shallow rooting zone of most boreal plants, even cool and moist sites at lower elevations are likely vulnerable to drought. For example the peak summer NDVI response following the 2004 drought was similar for adjacent cold and warm watershed basins. Thus, if frequent and severe summer droughts continue, moisture stress effects are likely to be widespread and prolonged throughout most of interior boreal Alaska, including relatively cool, moist sites regardless of spring snowpack conditions or spring phenology.

Can a healthy environment for all social groups be delivered through capitalism via market mechanisms? Or is it the capitalist system, itself, that has been at the root of the environmental and social crises we now face? This letter engages with this ongoing debate by drawing on material from a wider study, 'Achieving Environmental Justice', which examined the extent, form and causes of environmental justice and injustice in a range of countries with varying depths of marketization—United States, South Korea, United Kingdom, Sweden, China, Bolivia and Cuba. The analysis described here focuses on the interview material from this mixed methods study, drawing on over 140 interviews with officials, policy makers, and civil society leaders. The letter argues that there is an apparent propensity for capitalist processes to exacerbate, rather than reduce, environmental problems and inequities though the pursuit of relentless economic growth and profit accumulation. Therefore, we should perhaps let go of efforts to resolve environmental injustice within the constraints of capitalism and, instead, build an alternative economic system that can meet human needs in the context of a harmonious and respectful relationship with nature.

We analyzed a dataset from an experiment of an earth system model of intermediate complexity, focusing on the change in transient climate response to cumulative carbon emissions (TCRE) after atmospheric CO₂ concentration was stabilized in the Representative Concentration Pathway (RCP) 4.5. We estimated the TCRE in 2005 at 0.3–2.4 K/TtC for an unconstrained case and 1.1–1.7 K/TtC when constrained with historical and present-day observational data, the latter result being consistent with other studies. The range of TCRE increased when the increase of CO₂ concentration was moderated and then stabilized. This is because the larger (smaller) TCRE members yield even greater (less) TCRE. An additional experiment to assess the equilibrium state revealed significant changes in temperature and cumulative carbon emissions after 2300. We also found that variation of land carbon uptake is significant to the total allowable carbon emissions and subsequent change of the TCRE. Additionally, in our experiment, we revealed that equilibrium climate sensitivity (ECS), one of the 12 parameters perturbed in the ensemble experiment, has a strong positive relationship with the TCRE at the beginning of the stabilization and its subsequent change. We confirmed that for participant models in the Coupled Model Intercomparison Project Phase 5, ECS has a strong positive relationship with TCRE. For models using similar experimental settings, there is a positive relationship with TCRE for the start of the period of stabilization in CO₂ concentration, and rate of change after stabilization. The results of this study are influential regarding the total allowable carbon emissions calculated from the TCRE and the temperature increase set as the mitigation target.