Table of contents

Applying biochar to soil is thought to have multiple benefits, from helping mitigate climate change [1, 2], to managing waste [3] to conserving soil [4]. Biochar is also widely assumed to boost crop yield [5, 6], but there is controversy regarding the extent and cause of any yield benefit [7]. Here we use a global-scale meta-analysis to show that biochar has, on average, no effect on crop yield in temperate latitudes, yet elicits a 25% average increase in yield in the tropics. In the tropics, biochar increased yield through liming and fertilization, consistent with the low soil pH, low fertility, and low fertilizer inputs typical of arable tropical soils. We also found that, in tropical soils, high-nutrient biochar inputs stimulated yield substantially more than low-nutrient biochar, further supporting the role of nutrient fertilization in the observed yield stimulation. In contrast, arable soils in temperate regions are moderate in pH, higher in fertility, and generally receive higher fertilizer inputs, leaving little room for additional benefits from biochar. Our findings demonstrate that the yield-stimulating effects of biochar are not universal, but may especially benefit agriculture in low-nutrient, acidic soils in the tropics. Biochar management in temperate zones should focus on potential non-yield benefits such as lime and fertilizer cost savings, greenhouse gas emissions control, and other ecosystem services.

Anthropogenic land cover changes (LCC) affect regional and global climate through biophysical variations of the surface energy budget mediated by albedo, evapotranspiration, and roughness. This change in surface energy budget may exacerbate or counteract biogeochemical greenhouse gas effects of LCC, with a large body of emerging assessments being produced, sometimes apparently contradictory. We reviewed the existing scientific literature with the objective to provide an overview of the state-of-the-knowledge of the biophysical LCC climate effects, in support of the assessment of mitigation/adaptation land policies. Out of the published studies that were analyzed, 28 papers fulfilled the eligibility criteria, providing surface air temperature and/or precipitation change with respect to LCC regionally and/or globally. We provide a synthesis of the signal, magnitude and uncertainty of temperature and precipitation changes in response to LCC biophysical effects by climate region (boreal/temperate/tropical) and by key land cover transitions. Model results indicate that a modification of biophysical processes at the land surface has a strong regional climate effect, and non-negligible global impact on temperature. Simulations experiments of large-scale (i.e. complete) regional deforestation lead to a mean reduction in precipitation in all regions, while air surface temperature increases in the tropics and decreases in boreal regions. The net global climate effects of regional deforestation are less certain. There is an overall consensus in the model experiments that the average global biophysical climate response to complete global deforestation is atmospheric cooling and drying. Observed estimates of temperature change following deforestation indicate a smaller effect than model-based regional estimates in boreal regions, comparable results in the tropics, and contrasting results in temperate regions. Regional/local biophysical effects following LCC are important for local climate, water cycle, ecosystems, their productivity and biodiversity, and thus important to consider in the formulation of adaptation policy. However before considering the inclusion of biophysical climate effects of LCC under the UNFCCC, science has to provide robust tools and methods for estimation of both country and global level effects.

Global surface temperatures continue to rise. In most surface temperature data sets, the years 2014, 2015 and again 2016 set new global heat records since the start of regular measurements. Never before have three record years occurred in a row. We show that this recent streak of record heat does not in itself provide statistical evidence for an acceleration of global warming, nor was it preceded by a 'slowdown period' with a significantly reduced rate of warming. Rather, the data are fully consistent with a steady global warming trend since the 1970s, superimposed with random, stationary, short-term variability. All recent variations in short-term trends are well within what was to be expected, based on the observed warming trend and the observed variability from the 1970s up to the year 2000. We discuss some pitfalls of statistical analysis of global temperatures which have led to incorrect claims of an unexpected or significant warming slowdown.

In Indonesia, drought driven fires occur typically during the warm phase of the El Niño Southern Oscillation. This was the case of the events of 1997 and 2015 that resulted in months-long hazardous atmospheric pollution levels in Equatorial Asia and record greenhouse gas emissions.

Nonetheless, anomalously active fire seasons have also been observed in non-drought years. In this work, we investigated the impact of temperature on fires and found that when the July-October (JASO) period is anomalously dry, the sensitivity of fires to temperature is modest. In contrast, under normal-to-wet conditions, fire probability increases sharply when JASO is anomalously warm. This describes a regime in which an active fire season is not limited to drought years. Greater susceptibility to fires in response to a warmer environment finds support in the high evapotranspiration rates observed in normal-to-wet and warm conditions in Indonesia. We also find that fire probability in wet JASOs would be considerably less sensitive to temperature were not for the added effect of recent positive trends. Near-term regional climate projections reveal that, despite negligible changes in precipitation, a continuing warming trend will heighten fire probability over the next few decades especially in non-drought years. Mild fire seasons currently observed in association with wet conditions and cool temperatures will become rare events in Indonesia.

Irrigation is known to influence regional climate but most studies forecast and simulate irrigation with offline (i.e. land only) models. Using south eastern Australia as a test bed, we demonstrate that irrigation demand is fundamentally different between land only and land–atmosphere simulations. While irrigation only has a small impact on maximum temperature, the semi-arid environment experiences near surface moistening in coupled simulations over the irrigated regions, a feedback that is prevented in offline simulations. In land only simulations that neglect the local feedbacks, the simulated irrigation demand is 25% higher and the standard deviation of the mean irrigation rate is 60% smaller. These local-scale irrigation-driven feedbacks are not resolved in coarse-resolution climate models implying that use of these tools will overestimate irrigation demand. Future studies of irrigation demand must therefore account for the local land–atmosphere interactions by using coupled frameworks, at a spatial resolution that captures the key feedbacks.

Socio-economic shocks, technogenic catastrophes, and armed conflicts often have drastic impacts on local and regional food security through disruption of agricultural production and food trade, reduced investments, and deterioration of land and infrastructure. Recently, more research has focused on the effects of armed conflict on land systems, but still little is known about the processes and outcomes of such events. Here we use the case of Syria and Iraq and the seizure of land by the Islamic State (IS) since 2014 as an example of armed conflict, where we investigate the effects on agricultural land use. We apply a reproducible approach using 250 m satellite-based time-series data to quantify the areas under cultivation from 2000 to 2015. Despite a common belief about widespread land abandonment in areas under conflict, results point to multiple trajectories regarding cropland cultivation in the IS seized area: (1) expansion of cropland to formerly un-cultivated areas, (2) cropland abandonment, and (3) decrease of high-intensity cropland. Our study highlights the need to understand these diverse conflict-related and context-dependent changes to the land system.

Identifying the drivers of global crop price fluctuations is essential for estimating the risks of unexpected weather-induced production shortfalls and for designing optimal response measures. Here we show that with a consistent representation of storage dynamics, a simple supply–demand model can explain most of the observed variations in wheat prices over the last 40 yr solely based on time series of annual production and long term demand trends. Even the most recent price peaks in 2007/08 and 2010/11 can be explained by additionally accounting for documented changes in countries' trade policies and storage strategies, without the need for external drivers such as oil prices or speculation across different commodity or stock markets. This underlines the critical sensitivity of global prices to fluctuations in production. The consistent inclusion of storage into a dynamic supply-demand model closes an important gap when it comes to exploring potential responses to future crop yield variability under climate and land-use change.

We combine soil moisture (SM) data from AMSR-E and AMSR-2, and changes in terrestrial water storage (TWS) from time-variable gravity data from GRACE to delineate and characterize the evolution of drought and its impact on vegetation growth. GRACE-derived TWS provides spatially continuous observations of changes in overall water supply and regional drought extent, persistence and severity, while satellite-derived SM provides enhanced delineation of shallow-depth soil water supply. Together these data provide complementary metrics quantifying available plant water supply. We use these data to investigate the supply changes from water components at different depths in relation to satellite-based enhanced vegetation index (EVI) and gross primary productivity (GPP) from MODIS and solar-induced fluorescence (SIF) from GOME-2, during and following major drought events observed in the state of Texas, USA and its surrounding semiarid area for the past decade. We find that in normal years the spatial pattern of the vegetation–moisture relationship follows the gradient in mean annual precipitation. However since the 2011 hydrological drought, vegetation growth shows enhanced sensitivity to surface SM variations in the grassland area located in central Texas, implying that the grassland, although susceptible to drought, has the capacity for a speedy recovery. Vegetation dependency on TWS weakens in the shrub-dominated west and strengthens in the grassland and forest area spanning from central to eastern Texas, consistent with changes in water supply pattern. We find that in normal years GRACE TWS shows strong coupling and similar characteristic time scale to surface SM, while in drier years GRACE TWS manifests stronger persistence, implying longer recovery time and prolonged water supply constraint on vegetation growth. The synergistic combination of GRACE TWS and surface SM, along with remote-sensing vegetation observations provides new insights into drought impact on vegetation–moisture relationship, and unique information regarding vegetation resilience and the recovery of hydrological drought.

In several world regions, climate change is predicted to negatively affect crop productivity. The recent statistical yield literature emphasizes the importance of flexibly accounting for the distribution of growing-season temperature to better represent the effects of warming on crop yields. We estimate a flexible statistical yield model using a long panel from France to investigate the impacts of temperature and precipitation changes on wheat and barley yields. Winter varieties appear sensitive to extreme cold after planting. All yields respond negatively to an increase in spring–summer temperatures and are a decreasing function of precipitation about historical precipitation levels. Crop yields are predicted to be negatively affected by climate change under a wide range of climate models and emissions scenarios. Under warming scenario RCP8.5 and holding growing areas and technology constant, our model ensemble predicts a 21.0% decline in winter wheat yield, a 17.3% decline in winter barley yield, and a 33.6% decline in spring barley yield by the end of the century. Uncertainty from climate projections dominates uncertainty from the statistical model. Finally, our model predicts that continuing technology trends would counterbalance most of the effects of climate change.

Land surface phenology (LSP) derived from satellite data has been widely associated with recent global climate change. However, LSP is frequently influenced by land disturbances, which significantly limits our understanding of the phenological trends driven by climate change. Because wildfire is one of the most significant disturbance agents, we investigated the influences of wildfire on the start of growing season (SOS) and the interannual trends of SOS in the Hayman Fire area that occurred in 2002 in Colorado using time series of daily MODIS data (2001–2014). Results show that the Hayman Fire advanced the area-integrated SOS by 15.2 d and converted SOS from a delaying trend of 3.9 d/decade to an advancing trend of −1.9 d/decade during 2001–2014. The fire impacts on SOS increased from low burn severity to high burn severity. Moreover, the rate of increase of annual maximum and minimum EVI2 from 2003–2014 reflects that vegetation greenness could recover to pre-fire status in 2022 and 2053, respectively, which suggests that the fire impacts on the satellite-derived SOS variability and the interannual trends should continue in the next few decades.

Deforestation continues across the tropics at alarming rates, with repercussions for ecosystem processes, carbon storage and long term sustainability. Taking advantage of recent fine-scale measurement of deforestation, this analysis aims to improve our understanding of the scale of deforestation drivers in the tropics. We examined trends in forest clearings of different sizes from 2000–2012 by country, region and development level. As tropical deforestation increased from approximately 6900 kha yr⁻¹ in the first half of the study period, to >7900 kha yr⁻¹ in the second half of the study period, >50% of this increase was attributable to the proliferation of medium and large clearings (>10 ha). This trend was most pronounced in Southeast Asia and in South America. Outside of Brazil >60% of the observed increase in deforestation in South America was due to an upsurge in medium- and large-scale clearings; Brazil had a divergent trend of decreasing deforestation, >90% of which was attributable to a reduction in medium and large clearings. The emerging prominence of large-scale drivers of forest loss in many regions and countries suggests the growing need for policy interventions which target industrial-scale agricultural commodity producers. The experience in Brazil suggests that there are promising policy solutions to mitigate large-scale deforestation, but that these policy initiatives do not adequately address small-scale drivers. By providing up-to-date and spatially explicit information on the scale of deforestation, and the trends in these patterns over time, this study contributes valuable information for monitoring, and designing effective interventions to address deforestation.

Despite a continuous increase in well-mixed greenhouse gases, the global-mean surface temperature has shown a quasi-stabilization since 1998. This muted warming has been linked to the combined effects of internal climate variability and external forcing. The latter includes the impact of recent increase in the volcanic activity and of solar irradiance changes. Here we used a high-resolution coupled ocean–atmosphere climate model to assess the impact of the recent volcanic eruptions on the Earth's temperature, compared with the low volcanic activity of the early 2000s. Two sets of simulations are performed, one with realistic aerosol optical depth values, and the other with a fixed value of aerosol optical depth corresponding to a period of weak volcanic activity (1998–2002). We conclude that the observed recent increase in the volcanic activity led to a reduced warming trend (from 2003 to 2012) of 0.08 °C in ten years. The induced cooling is stronger during the last five-year period (2008–2012), with an annual global mean cooling of 0.04 °C (+/− 0.04 °C). The cooling is similar in summer (0.05 °C +/− 0.04 °C cooling) than in winter (0.03 °C +/− 0.04 °C cooling), but stronger in the Northern Hemisphere than in the Southern Hemisphere. Although equatorial and Arctic precipitation decreases in summer, the change in precipitation does not indicate robust changes at a local scale. Global heat content variations are found not to be impacted by the recent increase in volcanic activity.

More than half of the world's current population resides in urban areas, and cities account for roughly three-quarters of the total greenhouse gas emissions. Current and future trends in urbanization will have significant impacts on global climate. However, our collective understanding of the climate of urban areas remains deficient, which is mainly related to significant knowledge gaps in observations. The New York City Summer Heat Campaign was initiated to address some of these critical knowledge gaps. As part of the campaign the urban boundary layer over New York City was continuously monitored during July 2016, a period that witnessed three heatwave events. Surface weather stations and indoor sensors were also used to characterize the urban heat island intensity. Our results reveal that during the month, the urban heat island intensity was nearly twice compared to the decadal average. During the heatwave episodes, urban heat island intensities as high as 10 °C were observed. The thermal profiles indicate elevated temperatures in much of the boundary layer between 800–2500 m during the heatwave episodes. The profiles indicate a complex thermal structure and high intra-city variability. Thermal internal boundary layer was observed in neighborhoods populated by tall buildings. Overall the high-pressure system during the heatwave episodes acted as a thermal block and much of the heat generated in the urban surface layer remained within the boundary layer, thereby amplifying the near surface air temperature.

The relationship between the climate and agricultural production is of considerable importance to global food security. However, there has been relatively little exploration of climate-variability related yield shocks. The short observational yield record does not adequately sample natural inter-annual variability thereby limiting the accuracy of probability assessments. Focusing on the United States and China, we present an innovative use of initialised ensemble climate simulations and a new agro-climatic indicator, to calculate the risk of severe water stress. Combined, these regions provide 60% of the world's maize, and therefore, are crucial to global food security. To probe a greater range of inter-annual variability, the indicator is applied to 1400 simulations of the present day climate. The probability of severe water stress in the major maize producing regions is quantified, and in many regions an increased risk is found compared to calculations from observed historical data. Analysis suggests that the present day climate is also capable of producing unprecedented severe water stress conditions. Therefore, adaptation plans and policies based solely on observed events from the recent past may considerably under-estimate the true risk of climate-related maize shocks. The probability of a major impact event occurring simultaneously across both regions—a multi-breadbasket failure—is estimated to be up to 6% per decade and arises from a physically plausible climate state. This novel approach highlights the significance of climate impacts on crop production shocks and provides a platform for considerably improving food security assessments, in the present day or under a changing climate, as well as development of new risk based climate services.

While the EU Commission has encouraged Member States to combine national and international climate change mitigation measures with subnational environmental policies, there has been little harmonized effort towards the quantification of embodied greenhouse gas (GHG) emissions from household consumption across European regions. This study develops an inventory of carbon footprints associated with household consumption for 177 regions in 27 EU countries, thus, making a key contribution for the incorporation of consumption-based accounting into local decision-making. Footprint calculations are based on consumer expenditure surveys and environmental and trade detail from the EXIOBASE 2.3 multiregional input-output database describing the world economy in 2007 at the detail of 43 countries, 5 rest-of-the-world regions and 200 product sectors. Our analysis highlights the spatial heterogeneity of embodied GHG emissions within multiregional countries with subnational ranges varying widely between 0.6 and 6.5 tCO₂e/cap. The significant differences in regional contribution in terms of total and per capita emissions suggest notable differences with regards to climate change responsibility. The study further provides a breakdown of regional emissions by consumption categories (e.g. housing, mobility, food). In addition, our region-level study evaluates driving forces of carbon footprints through a set of socio-economic, geographic and technical factors. Income is singled out as the most important driver for a region's carbon footprint, although its explanatory power varies significantly across consumption domains. Additional factors that stand out as important on the regional level include household size, urban-rural typology, level of education, expenditure patterns, temperature, resource availability and carbon intensity of the electricity mix. The lack of cross-national region-level studies has so far prevented analysts from drawing broader policy conclusions that hold beyond national and regional borders.

Of the countries considering national-level policies for incentivizing reductions in forest-based greenhouse gas emissions (REDD+), some 25 are experiencing (or are emerging from) armed-conflicts. It has been hypothesized that the outcomes of the interactions between carbon-storage and peacebuilding efforts could result in either improved or worsened forest conservation and likewise increased or decreased conflict. Hence, for this study we explore potential interactions between forest carbon-storage and peacebuilding efforts, with Colombia as a case study. Spatial associations between biomass carbon and three conflict-related variables suggest that such interactions may exist. Nonetheless, while priority areas for carbon-focused conservation are presumably those at highest risks of deforestation, our research indicates that forests with lower risk of deforestation are typically those affected by armed-conflict. Our findings moreover highlight three possible roles played by Colombian forested municipalities in armed groups' military strategies: venues for battle, hideouts, and sources of natural resources to finance war.

A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential 'narco-capitalized' signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country- and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F = 9.90, p = 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio = 2.98, p = 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.

The Amazon basin is characterized by a strong interplay between the atmosphere and vegetation. Anthropogenic land use and land cover change (LULCC) affects vegetation and the exchange of energy and water with the atmosphere. Here we have assessed potential LULCC impacts on climate and natural vegetation dynamics over South America with a regional Earth system model that also accounts for vegetation dynamics. The biophysical and biogeochemical impacts from LULCC were addressed with two simulations over the CORDEX-South America domain. The results show that LULCC imposes local and remote influences on South American climate. These include significant local warming over the LULCC-affected area, changes in circulation patterns over the Amazon basin during the dry season, and an intensified hydrological cycle over much of the LULCC-affected area during the wet season. These changes affect the natural vegetation productivity which shows contrasting and significant changes between northwestern (around 10% increase) and southeastern (up to 10% decrease) parts of the Amazon basin caused by mesoscale circulation changes during the dry season, and increased productivity in parts of the LULCC-affected areas. We conclude that ongoing deforestation around the fringes of the Amazon could impact pristine forest by changing mesoscale circulation patterns, amplifying the degradation of natural vegetation caused by direct, local impacts of land use activities.

The impact of winter atmospheric blocking over the Ural Mountains region (UB) coincident with different phases of the North Atlantic Oscillation (NAO) on the sea ice variability over the Barents and Kara Seas (BKS) in winter is investigated. It is found that the UB in conjunction with the positive phase of the NAO (NAO⁺) leads to the strongest sea ice decline. During this phase composites and trajectory analyses reveal an efficient moisture pathway to the BKS from the mid-latitude North Atlantic near the Gulf Stream Extension region where water vapor is abundant due to high sea surface temperatures. The NAO⁺-UB combination is an optimal circulation pattern that significantly increases the BKS water vapor that plays a major role in the BKS warming and sea ice reduction, while the increased sensible and latent heat fluxes play secondary roles. By contrast, much fewer dramatic impacts on the BKS are observed when the UB coincides with the neutral or negative phases of the NAO.

Our results present new insights into the complex processes involved with Arctic sea ice reduction and warming. The mechanisms highlighted here potentially offer a perspective into the mechanisms behind Arctic multi-decadal climate variability.

Air quality policy to decrease fine particulate matter mass concentrations (PM_2.5) in the US has mainly targeted sulfate aerosol through controls on sulfur dioxide (SO₂) emissions. Organic aerosol (OA) instead of sulfate is now the dominant component of total PM_2.5. Long-term surface observations (1991–2013) in the Southeast US in summer show parallel decreases in sulfate (2.8%–4.0% a⁻¹) and OA (1.6%–1.9% a⁻¹). Decline of anthropogenic OA emissions is uncertain but is unlikely to fully explain this trend because most OA in the Southeast US in summer is biogenic. We conducted a 1991–2013 simulation with the GEOS-Chem chemical transport model including inventory decreases in anthropogenic SO₂, NO_x, and volatile organic compounds (VOCs) emissions, constant anthropogenic primary OA emissions, and a new mechanism of aqueous-phase SOA formation from isoprene. This simulation reproduces the observed long-term decreases of sulfate and OA, and attributes the OA decrease to decline in the OA yield from biogenic isoprene as sulfate decreases (driving lower aqueous aerosol volume and acidity). Interannual OA variability in the model (mainly driven by isoprene) is also well correlated with observations. This result provides support for a large air quality co-benefit of SO₂ emission controls in decreasing biogenic OA as well as sulfate.

We address the occurrence of the warm anomaly, known as the Blob, that developed from late 2013 to 2015 in the northeast Pacific and its connection with the El Niño–Southern Oscillation (ENSO) variability. The warm Blob results from the enhanced second ocean–atmosphere (O–A) coupled mode of variability in the tropical and North Pacific, representing a small part of the Victoria mode (VM) in the northeast Pacific forced by the strengthened North Pacific Oscillation-like atmospheric pattern since 2013. We also show that this second O–A mode reflects the meridional variability through the tropical–extratropical teleconnection and is an important precursor to the ENSO variability. The process is confirmed by the coupled patterns that evolved from late 2013 to 2016 and the multi-year persistence of the warm Blob. We emphasize the role of evolving basin-scale VM but not the warm Blob itself prior to the ENSO variability. Hence, the Blob and the most recent 2015/16 El Niño, which differs significantly from the other large El Niños in terms of the triggering hemisphere, are actually linked rather than independent phenomena.

In the midsummer of 2013, Central and Eastern China (CEC) was hit by an extraordinary heat event, with the region experiencing the warmest July–August on record. To explore how human-induced greenhouse gas emissions and natural internal variability contributed to this heat event, we compare observed July–August mean surface air temperature with that simulated by climate models. We find that both atmospheric natural variability and anthropogenic factors contributed to this heat event. This extreme warm midsummer was associated with a positive high-pressure anomaly that was closely related to the stochastic behavior of atmospheric circulation. Diagnosis of CMIP5 models and large ensembles of two atmospheric models indicates that human influence has substantially increased the chance of warm mid-summers such as 2013 in CEC, although the exact estimated increase depends on the selection of climate models.

Understanding long-term trends in aerosol loading and properties is essential for evaluating the health and climatic effects of these airborne particulates as well as the effectiveness of pollution control policies. While many studies have used satellite data to examine the trends in aerosol optical depth (AOD), very few have investigated the trends in aerosol properties associated with particle size, morphology, and light absorption. In this study, we investigate decadal-scale (13–15 year) trends in aerosol loading and properties during 2001–2015 over three populous regions: the Eastern United States (EUS), Western Europe (WEU), and Eastern and Central China (ECC). We use observations from MISR (Multi-angle Imaging SpectroRadiometer) and MODIS (Moderate resolution Imaging Spectroradiometer). Relationships between aerosol property trends and air pollutant emission changes are examined. We find that annual mean AOD shows pronounced decreasing trends over EUS and WEU regions, as a result of considerable emission reductions in all major pollutants except for mineral dust and ammonia (NH₃). Over the ECC region, AOD increases before 2006 due to emission increases induced by rapid economic development, fluctuates between 2006 and 2011, and subsequently decreases after 2011 in conjunction with effective emission reduction in anthropogenic primary aerosols, sulfur dioxide (SO₂), and nitrogen oxides (NO_x). The fraction of small-size AOD (<0.7 μm diameter), Ångstrom exponent and single-scattering albedo have generally decreased, while the fractions of large-size (>1.4 μm diameter), nonspherical and absorbing AOD have generally shown increasing trends over EUS and WEU regions, indicating that fine and light-scattering aerosol constituents have been more effectively reduced than coarse and light-absorbing constituents. These trends are consistent with the larger reduction ratios in SO₂ and NO_x emissions than in primary aerosols, including mineral dust and black carbon (BC). Over the ECC region, no significant trends are observed with respect to size distribution, morphology, or light absorption, which we attribute to a simultaneous increase in emissions of SO₂, NO_x, and primary aerosols including BC before 2006, and a simultaneous decrease after 2011. This study demonstrates the importance and usefulness of satellite-borne sensors, particularly MISR, in association with evaluating the effectiveness of air pollution control policies.

Climate change will increase the number and severity of heat waves, and is expected to negatively affect crop yields. Here we show for wheat and maize across Europe that heat stress is considerably reduced by irrigation due to surface cooling for both current and projected future climate. We demonstrate that crop heat stress impact assessments should be based on canopy temperature because simulations with air temperatures measured at standard weather stations cannot reproduce differences in crop heat stress between irrigated and rainfed conditions. Crop heat stress was overestimated on irrigated land when air temperature was used with errors becoming larger with projected climate change. Corresponding errors in mean crop yield calculated across Europe for baseline climate 1984–2013 of 0.2 Mg yr⁻¹ (2%) and 0.6 Mg yr⁻¹ (5%) for irrigated winter wheat and irrigated grain maize, respectively, would increase to up to 1.5 Mg yr⁻¹ (16%) for irrigated winter wheat and 4.1 Mg yr⁻¹ (39%) for irrigated grain maize, depending on the climate change projection/GCM combination considered. We conclude that climate change impact assessments for crop heat stress need to account explicitly for the impact of irrigation.

Humans are biophysically connected to the biosphere through the flows of materials and energy appropriated from ecosystems. While this connection is fundamental for human well-being, many modern societies have—for better or worse—disconnected themselves from the natural productivity of their immediate regional environment. In this paper, we conceptualize the biophysical human–nature connectedness of land use systems at regional scales. We distinguish two mechanisms by which primordial connectedness of people to regional ecosystems has been circumvented via the use of external inputs. First, 'biospheric disconnection' refers to people drawing on non-renewable minerals from outside the biosphere (e.g. fossils, metals and other minerals). Second, 'spatial disconnection' arises from the imports and exports of biomass products and imported mineral resources used to extract and process ecological goods. Both mechanisms allow for greater regional resource use than would be possible otherwise, but both pose challenges for sustainability, for example, through waste generation, depletion of non-renewable resources and environmental burden shifting to distant regions. In contrast, biophysically reconnected land use systems may provide renewed opportunities for inhabitants to develop an awareness of their impacts and fundamental reliance on ecosystems. To better understand the causes, consequences, and possible remedies related to biophysical disconnectedness, new quantitative methods to assess the extent of regional biophysical human–nature connectedness are needed. To this end, we propose a new methodological framework that can be applied to assess biophysical human–nature connectedness in any region of the world.

We performed an intercomparison of river discharge regulated by dams under four meteorological forcings among five global hydrological models for a historical period by simulation. This is the first global multimodel intercomparison study on dam-regulated river flow. Although the simulations were conducted globally, the Missouri–Mississippi and Green–Colorado Rivers were chosen as case-study sites in this study. The hydrological models incorporate generic schemes of dam operation, not specific to a certain dam. We examined river discharge on a longitudinal section of river channels to investigate the effects of dams on simulated discharge, especially at the seasonal time scale. We found that the magnitude of dam regulation differed considerably among the hydrological models. The difference was attributable not only to dam operation schemes but also to the magnitude of simulated river discharge flowing into dams. That is, although a similar algorithm of dam operation schemes was incorporated in different hydrological models, the magnitude of dam regulation substantially differed among the models. Intermodel discrepancies tended to decrease toward the lower reaches of these river basins, which means model dependence is less significant toward lower reaches. These case-study results imply that, intermodel comparisons of river discharge should be made at different locations along the river's course to critically examine the performance of hydrological models because the performance can vary with the locations.

Potential climate drivers of Arctic tundra vegetation productivity are investigated to understand recent greening and browning trends documented by maximum normalized difference vegetation index (NDVI) (MaxNDVI) and time-integrated NDVI (TI-NDVI) for 1982–2015. Over this period, summer sea ice has continued to decline while oceanic heat content has increased. The increases in summer warmth index (SWI) and NDVI have not been uniform over the satellite record. SWI increased from 1982 to the mid-1990s and remained relatively flat from 1998 onwards until a recent upturn. While MaxNDVI displays positive trends from 1982–2015, TI-NDVI increased from 1982 until 2001 and has declined since. The data for the first and second halves of the record were analyzed and compared spatially for changing trends with a focus on the growing season. Negative trends for MaxNDVI and TI-NDVI were more common during 1999–2015 compared to 1982–1998.

Trend analysis within the growing season reveals that sea ice decline was larger in spring for the 1982–1998 period compared to 1999–2015, while fall sea ice decline was larger in the later period. Land surface temperature trends for the 1982–1998 growing season are positive and for 1999–2015 are positive in May–June but weakly negative in July–August. Spring biweekly NDVI trends are positive and significant for 1982–1998, consistent with increasing open water and increased available warmth in spring. MaxNDVI trends for 1999–2015 display significant negative trends in May and the first half of June.

Numerous possible drivers of early growing season NDVI decline coincident with warming temperatures are discussed, including increased standing water, delayed spring snow-melt, winter thaw events, and early snow melt followed by freezing temperatures. Further research is needed to robustly identify drivers of the spring NDVI decline.

Long-term human disturbance of tropical forests may favor generalist plant species leading to biotic homogenization. We aimed to a) assess if generalist species dominate across different successional ages and topographical positions in a tropical dry forest with a long history of human disturbance, b) to characterize functional traits associated with generalist and specialist species, and c) to assess if a predominance of generalists leads to a homogeneous functional structure across the landscape. We used a multinomial model of relative abundances to classify 118 woody species according to their successional/topographic habitat. Three species were classified as secondary-forest specialists, five as mature-forest specialists, 35 as generalists, and 75 as too rare to classify. According to topography, six species were hill specialists, eight flat-site specialists, 35 generalists, and 70 too rare. Generalists dominated across the landscape. Analysis of 14 functional traits from 65 dominant species indicated that generalists varied from acquisitive strategies of light and water early in succession to conservative strategies in older forests and on hills. Long-term human disturbance may have favored generalist species, but this did not result in functional homogenization. Further analyses considering other functional traits, and temporal and fine-scale microenvironmental variation are needed to better understand community assembly.