Table of contents

Climate change is a risk management challenge for society, with uncertain but potentially severe outcomes affecting natural and human systems, across generations. Managing climate-related risks will be more difficult without a base of knowledge and practice aimed at identifying and evaluating specific risks, and their likelihood and consequences, as well as potential actions to promote resilience in the face of these risks. We suggest three improvements to the process of conducting climate change assessments to better characterize risk and inform risk management actions.

Northern Eurasia is made up of a complex and diverse set of physical, ecological, climatic and human systems, which provide important ecosystem services including the storage of substantial stocks of carbon in its terrestrial ecosystems. At the same time, the region has experienced dramatic climate change, natural disturbances and changes in land management practices over the past century. For these reasons, Northern Eurasia is both a critical region to understand and a complex system with substantial challenges for the modeling community. This review is designed to highlight the state of past and ongoing efforts of the research community to understand and model these environmental, socioeconomic, and climatic changes. We further aim to provide perspectives on the future direction of global change modeling to improve our understanding of the role of Northern Eurasia in the coupled human–Earth system. Modeling efforts have shown that environmental and socioeconomic changes in Northern Eurasia can have major impacts on biodiversity, ecosystems services, environmental sustainability, and the carbon cycle of the region, and beyond. These impacts have the potential to feedback onto and alter the global Earth system. We find that past and ongoing studies have largely focused on specific components of Earth system dynamics and have not systematically examined their feedbacks to the global Earth system and to society. We identify the crucial role of Earth system models in advancing our understanding of feedbacks within the region and with the global system. We further argue for the need for integrated assessment models (IAMs), a suite of models that couple human activity models to Earth system models, which are key to address many emerging issues that require a representation of the coupled human–Earth system.

Despite the well-established links between air pollution and human health, vegetation, and aquatic ecosystems, less attention has been paid to the potential impact of reactive atmospheric gases and aerosols on avian species. In this literature review, we summarize findings published since 1950 regarding avian responses to air pollution and discuss knowledge gaps that could be addressed in future studies. We find consistent evidence for adverse health impacts on birds attributable to exposure to gas-phase and particulate air pollutants, including carbon monoxide (CO), ozone (O₃), sulfur dioxide (SO₂), smoke, and heavy metals, as well as mixtures of urban and industrial emissions. Avian responses to air pollution include respiratory distress and illness, increased detoxification effort, elevated stress levels, immunosuppression, behavioral changes, and impaired reproductive success. Exposure to air pollution may furthermore reduce population density, species diversity, and species richness in bird communities.

Tropospheric ozone (O₃), a harmful secondary air pollutant, can affect the climate via direct radiative forcing and by modifying the radiative forcing of aerosols through its role as an atmospheric oxidant. Moreover, O₃ exerts a strong oxidative pressure on the biosphere and indirectly influences the climate by altering the materials and energy exchange between terrestrial ecosystems and the atmosphere. However, the magnitude by which O₃ affects the global budgets of greenhouse gases (GHGs: CO₂, CH₄, and N₂O) through altering the land–atmosphere exchange is largely unknown. Here we assess the sensitivity of these budgets to tropospheric O₃ pollution based on a meta-analysis of experimental studies on the effects of elevated O₃ on GHG exchange between terrestrial ecosystems and the atmosphere. We show that across ecosystems, elevated O₃ suppresses N₂O emissions and both CH₄ emissions and uptake, and has little impact on stimulation of soil CO₂ emissions except at relatively high concentrations. Therefore, the soil system would be transformed from a sink into a source of GHGs with O₃ levels increasing. The global atmospheric budget of GHGs is sensitive to O₃ pollution largely because of the carbon dioxide accumulation resulting from suppressed vegetation carbon uptake; the negative contributions from suppressed CH₄ and N₂O emissions can offset only ∼10% of CO₂ emissions from the soil–vegetation system. Based on empirical data, this work, though with uncertainties, provides the first assessment of sensitivity of global budgets of GHGs to O₃ pollution, representing a necessary step towards fully understanding and evaluating O₃–climate feedbacks mediated by the biosphere.

Despite progress in impact modelling, communicating and understanding the implications of climatic change projections is challenging due to inherent complexity and a cascade of uncertainty. In this letter, we present an alternative representation of global climate change projections based on shifts in 125 multivariate strata characterized by relatively homogeneous climate. These strata form climate analogues that help in the interpretation of climate change impacts. A Random Forests classifier was calculated and applied to 63 Coupled Model Intercomparison Project Phase 5 climate scenarios at 5 arcmin resolution. Results demonstrate how shifting bioclimate strata can summarize future environmental changes and form a middle ground, conveniently integrating current knowledge of climate change impact with the interpretation advantages of categorical data but with a level of detail that resembles a continuous surface at global and regional scales. Both the agreement in major change and differences between climate change projections are visually combined, facilitating the interpretation of complex uncertainty. By making the data and the classifier available we provide a climate service that helps facilitate communication and provide new insight into the consequences of climate change.

We have studied the influence of offshore marine constructions on the moon jellyfish population in the Adriatic sea, where the newly set up substrates enable the formation of a new population based in the formerly unpopulated open waters. Our five-year long computer simulation uses a high resolution coupled bio-physical individual-based model to track the dispersal of the offspring from subpopulations originating from offshore and shore-based sources. According to our study, the platforms enhance connectivity between subpopulations of jellyfish polyps, help sustain existing shore-based subpopulations, contribute to jellyfish blooms in some areas, and play an important role in establishing connection with the rest of the Mediterranean, in addition to representing substantial amounts of available substrate. This is an aspect that is usually overlooked when evaluating the ecological impact of existing and future wind farms, oil and gas platforms, etc. Our approach could serve as a role model in future studies of ecological impacts of planned offshore constructions.

The concept of spatial climate analogs, that is identifying a place with a present-day climate similar to the projections of a place of interest, is a promising method for visualizing and communicating possible effects of climate change. We show that when accounting for seasonal cycles of both temperature and precipitation, it is impossible to find good analogs for projections at many places across the world. For substantial land fractions, primarily in the tropics and subtropics, there are no analogs anywhere with current seasonal cycles of temperature and precipitation matching their projected future conditions. This implies that these places experience the emergence of novel climates. For 1.5 °C global warming about 15% and for 2 °C warming about 21% of the global land is projected to experience novel climates, whereas for a 4 °C warming the corresponding novel climates may emerge on more than a third of the global land fraction. Similar fractions of today's climates, mainly found in the tropics, subtropics and polar north, are anticipated to disappear in the future. Note that the exact quantification of the land fraction is sensitive to the threshold selection. Novel and disappearing climates may have serious consequences for impacts that are sensitive to the full seasonal cycle of temperature and precipitation. For individual seasons, however, spatial analogs may still be a powerful tool for climate change communication.

The continuing decline in Arctic sea-ice will likely lead to increased human activity and opportunities for shipping in the region, suggesting that seasonal predictions of route openings will become ever more important. Here we present results from a set of 'perfect model' experiments to assess the predictability characteristics of the opening of Arctic sea routes. We find skilful predictions of the upcoming summer shipping season can be made from as early as January, although typically forecasts show lower skill before a May 'predictability barrier'. We demonstrate that in forecasts started from January, predictions of route opening date are twice as uncertain as predicting the closing date and that the Arctic shipping season is becoming longer due to climate change, with later closing dates mostly responsible. We find that predictive skill is state dependent with predictions for high or low ice years exhibiting greater skill than medium ice years. Forecasting the fastest open water route through the Arctic is accurate to within 200 km when predicted from July, a six-fold increase in accuracy compared to forecasts initialised from the previous November, which are typically no better than climatology. Finally we find that initialisation of accurate summer sea-ice thickness information is crucial to obtain skilful forecasts, further motivating investment into sea-ice thickness observations, climate models, and assimilation systems.

Seasonal climate forecasts could be an important planning tool for farmers, government and insurance companies that can lead to better and timely management of seasonal climate risks. However, climate seasonal forecasts are often under-used, because potential users are not well aware of the capabilities and limitations of these products. This study aims at assessing the merits and caveats of a statistical empirical method, the ensemble streamflow prediction system (ESP, an ensemble based on reordering historical data) and an operational dynamical forecast system, the European Centre for Medium-Range Weather Forecasts—System 4 (S4) in predicting summer drought in Europe. Droughts are defined using the Standardized Precipitation Evapotranspiration Index for the month of August integrated over 6 months. Both systems show useful and mostly comparable deterministic skill. We argue that this source of predictability is mostly attributable to the observed initial conditions. S4 shows only higher skill in terms of ability to probabilistically identify drought occurrence. Thus, currently, both approaches provide useful information and ESP represents a computationally fast alternative to dynamical prediction applications for drought prediction.

Urban vegetation provides many highly valued ecosystem services but also requires extensive urban water resources. Increasingly, cities are experiencing water limitations and managing outdoor urban water use is an important concern. Quantifying the water lost via evapotranspiration (ET) is critical for urban water management and conservation, especially in arid or semi-arid regions. In this study, we deployed a mobile energy balance platform to measure evaporative fraction throughout Riverside, California, a warm, semi-arid, city. We observed the relationship between evaporative fraction and satellite derived vegetation index across 29 sites, which was then used to map whole-city ET for a representative mid-summer period. Resulting ET distributions were strongly associated with both neighborhood population density and income. By comparing 2014 and 2015 summer-period water uses, our results show 7.8% reductions in evapotranspiration, which were also correlated with neighborhood demographic characteristics. Our findings suggest a mobile energy balance measurement platform coupled with satellite imagery could serve as an effective tool in assessing the outdoor water use at neighborhood to whole city scales.

Linking annual tree growth with remotely-sensed terrestrial vegetation indices provides a basis for using tree rings as proxies for ecosystem primary productivity over large spatial and long temporal scales. In contrast with most previous tree ring/remote sensing studies that have focused on temperature-limited boreal and taiga environments, here we compare the normalized difference vegetation index (NDVI) with a network of Pinus brutia tree ring width chronologies collected along ecological gradients in semiarid Cyprus, where both radial tree growth and broader vegetation activity are controlled by drought. We find that the interaction between precipitation, elevation, and land-cover type generate a relationship between radial tree growth and NDVI. While tree ring chronologies at higher-elevation forested sites do not exhibit climate-driven linkages with NDVI, chronologies at lower-elevation dry sites are strongly correlated with NDVI during the winter precipitation season. At lower-elevation sites, land cover is dominated by grasslands and shrublands and tree ring widths operate as a proxy for ecosystem-scale vegetation activity. Tree rings can therefore be used to reconstruct productivity in water-limited grasslands and shrublands, where future drought stress is expected to alter the global carbon cycle, biodiversity, and ecosystem functioning in the 21st century.

California's climate is characterized by the largest precipitation and streamflow variability observed within the conterminous US This, combined with chronic groundwater overdraft of 0.6–3.5 km³ yr⁻¹, creates the need to identify additional surface water sources available for groundwater recharge using methods such as agricultural groundwater banking, aquifer storage and recovery, and spreading basins. High-magnitude streamflow, i.e. flow above the 90th percentile, that exceeds environmental flow requirements and current surface water allocations under California water rights, could be a viable source of surface water for groundwater banking. Here, we present a comprehensive analysis of the magnitude, frequency, duration and timing of high-magnitude streamflow (HMF) for 93 stream gauges covering the Sacramento, San Joaquin and Tulare basins in California. The results show that in an average year with HMF approximately 3.2 km³ of high-magnitude flow is exported from the entire Central Valley to the Sacramento-San Joaquin Delta often at times when environmental flow requirements of the Delta and major rivers are exceeded. High-magnitude flow occurs, on average, during 7 and 4.7 out of 10 years in the Sacramento River and the San Joaquin-Tulare Basins, respectively, from just a few storm events (5–7 1-day peak events) lasting for 25–30 days between November and April. The results suggest that there is sufficient unmanaged surface water physically available to mitigate long-term groundwater overdraft in the Central Valley.

Southern Ocean sea-ice cover exerts critical control on local albedo and Antarctic precipitation, but simulated Antarctic sea-ice concentration commonly disagrees with observations. Here we show that the radiative effects of precipitating ice (falling snow) contribute substantially to this discrepancy. Many models exclude these radiative effects, so they underestimate both shortwave albedo and downward longwave radiation. Using two simulations with the climate model CESM1, we show that including falling-snow radiative effects improves the simulations relative to cloud properties from CloudSat-CALIPSO, radiation from CERES-EBAF and sea-ice concentration from passive microwave sensors. From 50–70°S, the simulated sea-ice-area bias is reduced by 2.12 × 10⁶ km² (55%) in winter and by 1.17 × 10⁶ km² (39%) in summer, mainly because increased wintertime longwave heating restricts sea-ice growth and so reduces summer albedo. Improved Antarctic sea-ice simulations will increase confidence in projected Antarctic sea level contributions and changes in global warming driven by long-term changes in Southern Ocean feedbacks.

Arctic sea ice over the last few decades has experienced a significant decline in coverage both in summer and winter. The currently warming Atlantic Water layer has a pronounced impact on sea ice in the Nordic Seas (including the Barents Sea). More open water combined with the prevailing atmospheric pattern of airflow from the southeast, and persistent North Atlantic storms such as the recent extremely strong Storm Frank in December 2015, lead to increased energy transport to the high Arctic. Each of these storms brings sizeable anomalies of heat to the high Arctic, resulting in significant warming and slowing down of sea ice growth or even melting. Our analysis indicates that the recently observed sea ice decline in the Nordic Seas during the cold season around Svalbard, Franz Joseph Land and Novaya Zemlya, and the associated heat release from open water into the atmosphere, contributed significantly to the increase in the downward longwave radiation throughout the entire Arctic. Added to other changes in the surface energy budget, this increase since the 1960s to the present is estimated to be at least 10 W m⁻², which can result in thinner (up to at least 15–20 cm) Arctic ice at the end of the winter. This change in the surface budget is an important contributing factor accelerating the thinning of Arctic sea ice.

Climate variability is shown to be an important driver of spatial and temporal changes in hydrometereological variables in Europe. However, the influence of climate variability on flood damage has received little attention. We investigated the El Niño Southern Oscillation (ENSO), the North Atlantic Oscillation (NAO), and the East Atlantic pattern (EA) during their neutral, positive, and negative phases, to understand their relationships with four flood indicators: Occurrence of Extreme Rainfall, Intensity of Extreme Rainfall, Flood Occurrence, and Flood Damage. We found that positive and negative phases of NAO and EA are associated with more (or less) frequent and intense seasonal extreme rainfall over large areas of Europe. The relationship between ENSO and the Occurrence of Extreme Rainfall and Intensity of Extreme Rainfall in Europe is much smaller than the relationship with NAO or EA, but still significant in some regions. We show that Flood Damage and Flood Occurrence have strong links with climate variability, especially in southern and eastern Europe. Therefore, when investigating flooding across Europe, all three indices of climate variability should be considered. Future research should focus on their joint influence on flood risk. The potential inclusion of seasonal forecasts of indices of climate variability could be effective in forecasting flood damage.

Consumers in the US market and across the globe are beginning to widely adopt light emitting diode (LED) lighting products while the technology continues to undergo significant changes. While LED products are evolving to consume less energy, they are also more complex than traditional lighting products with a higher number of parts and a larger number of electronic components. Enthusiasm around the efficiency and long expected life span of LED lighting products is valid, but research to optimize product characteristics and design is needed. This study seeks to address that gap by characterizing LED lighting products' suitability for end of life (EOL) recycling and disposal. The authors disassembled and assessed 17 different lighting products to understand how designs differ between brands and manufacture year. Products were evaluated based on six parameters to quantify the design. The analysis indicates that while the efficiency of LED products has improved dramatically in the recent past, product designers and manufacturers could incorporate design strategies to improve environmental performance of lighting products at end-of-life.

Mexico's government enacted an energy reform in 2013 that aims to foster competitiveness and private investment throughout the energy sector value chain. As part of this reform, it is expected that extraction of oil and gas via hydraulic fracturing will increase in five shale basins (e.g. Burgos, Sabinas, Tampico, Tuxpan, and Veracruz). Because hydraulic fracturing is a water-intensive activity, it is relevant to assess the potential water availability for this activity in Mexico. This research aims to quantify the water availability for hydraulic fracturing in Mexico and identify its spatial distribution along the five shale basins. The methodology consisted of a multilayer geospatial analysis that overlays the water availability in the watersheds and aquifers with the different types of shale resources areas (e.g. oil and associated gas, wet gas and condensate, and dry gas) in the five shale basins. The aquifers and watersheds in Mexico are classified in four zones depending on average annual water availability. Three scenarios were examined based on different impact level on watersheds and aquifers from hydraulic fracturing. For the most conservative scenario analyzed, the results showed that the water available could be used to extract between 8.15 and 70.42 Quadrillion British thermal units (Quads) of energy in the typical 20–30 year lifetime of the hydraulic fracturing wells that could be supplied with the annual water availability overlaying the shale areas, with an average across estimates of around 18.05 Quads. However, geographic variation in water availability could represent a challenge for extracting the shale reserves. Most of the water available is located closer to the Gulf of Mexico, but the areas with the larger recoverable shale reserves coincide with less water availability in Northern Mexico. New water management techniques (such as recycling and re-use), more efficient fracturing methods, shifts in usage patterns, or other water sources need to be identified to allocate water for hydraulic fracturing without affecting current users (e.g. municipal, irrigation, industrial, and environmental flows).

Historical changes in soil carbon associated with land-use change (LUC) result mainly from the changes in the quantity of litter inputs to the soil and the turnover of carbon in soils. We use a factor separation technique to assess how the input-driven and turnover-driven controls, as well as their synergies, have contributed to historical changes in soil carbon associated with LUC. We apply this approach to equilibrium simulations of present-day and pre-industrial land use performed using the dynamic global vegetation model JSBACH. Our results show that both the input-driven and turnover-driven changes generally contribute to a gain in soil carbon in afforested regions and a loss in deforested regions. However, in regions where grasslands have been converted to croplands, we find an input-driven loss that is partly offset by a turnover-driven gain, which stems from a decrease in the fire-related carbon losses. Omitting land management through crop and wood harvest substantially reduces the global losses through the input-driven changes. Our study thus suggests that the dominating control of soil carbon losses is via the input-driven changes, which are more directly accessible to human management than the turnover-driven ones.

Deep decarbonization of the global energy system will require large investments in energy innovation and the deployment of new technologies. While many studies have focused on the expenditure that will be needed, here we focus on how government has spent public sector resources on innovation for a key carbon-free technology: advanced nuclear. We focus on nuclear power because it has been contributing almost 20% of total US electric generation, and because the US program in this area has historically been the world's leading effort. Using extensive data acquired through the Freedom of Information Act, we reconstruct the budget history of the Department of Energy's program to develop advanced, non-light water nuclear reactors. Our analysis shows that—despite spending $2 billion since the late 1990s—no advanced design is ready for deployment. Even if the program had been well designed, it still would have been insufficient to demonstrate even one non-light water technology. It has violated much of the wisdom about the effective execution of innovative programs: annual funding varies fourfold, priorities are ephemeral, incumbent technologies and fuels are prized over innovation, and infrastructure spending consumes half the budget. Absent substantial changes, the possibility of US-designed advanced reactors playing a role in decarbonization by mid-century is low.

Unprecedented decreases in atmospheric nitrogen (N) deposition together with increases in agricultural N-use efficiency have led to decreases in net anthropogenic N inputs in many eastern US and Canadian watersheds as well as in Europe. Despite such decreases, N concentrations in streams and rivers continue to increase, and problems of coastal eutrophication remain acute. Such a mismatch between N inputs and outputs can arise due to legacy N accumulation and subsequent lag times between implementation of conservation measures and improvements in water quality. In the present study, we quantified such lag times by pairing long-term N input trajectories with stream nitrate concentration data for 16 nested subwatersheds in a 6800 km², Southern Ontario watershed. Our results show significant nonlinearity between N inputs and outputs, with a strong hysteresis effect indicative of decadal-scale lag times. The mean annual lag time was found to be 24.5 years, with lags varying seasonally, likely due to differences in N-delivery pathways. Lag times were found to be negatively correlated with both tile drainage and watershed slope, with tile drainage being a dominant control in fall and watershed slope being significant during the spring snowmelt period. Quantification of such lags will be crucial to policy-makers as they struggle to set appropriate goals for water quality improvement in human-impacted watersheds.

The Southeast Asian region had been subjected to a drastic reduction in air quality from the biomass burnings that occurred in 2013 and 2015. The smoke from the biomass burnings covered the entire region including Brunei, Indonesia, Malaysia, Singapore and Thailand, with haze particulate matter (PM) reducing the air quality to hazardous levels. Here we report a comprehensive size–composition–morphology characterization of the PM collected from an urban site in Singapore during the two haze events. The two haze events were a result of biomass burning and occurred in two different geographical source regions. We show the similarities and variations of particle size distribution during hazy and clear days during the two haze events. Sub-micron particles (<1 μm) dominate (∼50%) the aerosols in the atmosphere during clear and hazy days. Using electron microscopy, we also categorize the PM, namely soot, organic–inorganic clusters and hybrid particles. The composition and morphology were similar in both the haze events. The majority of the PM is composed of carbon (∼51%) and other elements pertaining to the earth's crust. The complexity of the mixing state of the PM is highlighted and the role of the capture mode is addressed. We also present the morphological characterization of all the classified PM. The box counting method is used to determine the fractal dimensions of the PM, and the dimensionality varied for every classification from 1.79 to 1.88. We also report the complexities of particles and inconsistencies in the existing approaches to understand them.

This paper assesses whether ExxonMobil Corporation has in the past misled the general public about climate change. We present an empirical document-by-document textual content analysis and comparison of 187 climate change communications from ExxonMobil, including peer-reviewed and non-peer-reviewed publications, internal company documents, and paid, editorial-style advertisements ('advertorials') in The New York Times. We examine whether these communications sent consistent messages about the state of climate science and its implications—specifically, we compare their positions on climate change as real, human-caused, serious, and solvable. In all four cases, we find that as documents become more publicly accessible, they increasingly communicate doubt. This discrepancy is most pronounced between advertorials and all other documents. For example, accounting for expressions of reasonable doubt, 83% of peer-reviewed papers and 80% of internal documents acknowledge that climate change is real and human-caused, yet only 12% of advertorials do so, with 81% instead expressing doubt. We conclude that ExxonMobil contributed to advancing climate science—by way of its scientists' academic publications—but promoted doubt about it in advertorials. Given this discrepancy, we conclude that ExxonMobil misled the public. Our content analysis also examines ExxonMobil's discussion of the risks of stranded fossil fuel assets. We find the topic discussed and sometimes quantified in 24 documents of various types, but absent from advertorials. Finally, based on the available documents, we outline ExxonMobil's strategic approach to climate change research and communication, which helps to contextualize our findings.

Simulating vegetation photosynthetic productivity (or gross primary production, GPP) is a critical feature of the biome models used for impact assessments of climate change. We conducted a benchmarking of global GPP simulated by eight biome models participating in the second phase of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP2a) with four meteorological forcing datasets (30 simulations), using independent GPP estimates and recent satellite data of solar-induced chlorophyll fluorescence as a proxy of GPP. The simulated global terrestrial GPP ranged from 98 to 141 Pg C yr⁻¹ (1981–2000 mean); considerable inter-model and inter-data differences were found. Major features of spatial distribution and seasonal change of GPP were captured by each model, showing good agreement with the benchmarking data. All simulations showed incremental trends of annual GPP, seasonal-cycle amplitude, radiation-use efficiency, and water-use efficiency, mainly caused by the CO₂ fertilization effect. The incremental slopes were higher than those obtained by remote sensing studies, but comparable with those by recent atmospheric observation. Apparent differences were found in the relationship between GPP and incoming solar radiation, for which forcing data differed considerably. The simulated GPP trends co-varied with a vegetation structural parameter, leaf area index, at model-dependent strengths, implying the importance of constraining canopy properties. In terms of extreme events, GPP anomalies associated with a historical El Niño event and large volcanic eruption were not consistently simulated in the model experiments due to deficiencies in both forcing data and parameterized environmental responsiveness. Although the benchmarking demonstrated the overall advancement of contemporary biome models, further refinements are required, for example, for solar radiation data and vegetation canopy schemes.

In seasonal plant communities, it is recognized that topography-related variation in water availability and solar radiation determine vegetation structure and community composition; however, the effects on functional structure, particularly through changes in resource use strategies of plants are still poorly understood. This study examines the effects of slope aspect and topographic position on functional trait dominance in a tropical dry forest landscape and explores whether strategies for coping with drought (avoidance vs. tolerance) segregate spatially along the water stress gradient created by the interaction of these two topographic factors. The study was conducted in the Balsas river basin in south-central Mexico. Functional traits were evaluated in 63 species of trees (≥ 2.5 cm diameter at breast height) dominant in plots located at three topographic positions (low, medium and high) and on two slope aspects (north and south). Eight leaf and four stem functional traits, relating to the plants' ability to avoid or tolerate water and temperature stress, were measured. Community-level functional traits were strongly affected by topographic position while only a weak signal was detected by the slope aspect. Contrary to our expectations, attributes associated with drought tolerance predominated on the lower topographic positions of the slopes, (moister and warmer sites), while on the upper parts with drier soil, but cooler air, attributes associated with water stress avoidance dominated. In addition, variation in the dominance of leaf pulvini and trichomes along the topographic gradient suggests environmental filtering by elevated air temperatures and water stress, respectively. Overall, our results suggest that the upper topographic positions that generate a shorter and more fluctuating water-availability window, favor readily-deciduous plants with high levels of water storage in their tissues, traits allowing for a rapid avoid of water stress, whereas on the lower topographic positions, where the soil remains moist for longer periods of time, tardily-deciduous species thrive with dense, low-water content tissues, attributes that are associated with physiological tolerance to drought.

In September 2015, the United Nations General Assembly adopted Agenda 2030, which comprises a set of 17 Sustainable Development Goals (SDGs) defined by 169 targets. 'Ensuring access to affordable, reliable, sustainable and modern energy for all by 2030' is the seventh goal (SDG7). While access to energy refers to more than electricity, the latter is the central focus of this work. According to the World Bank's 2015 Global Tracking Framework, roughly 15% of the world's population (or 1.1 billion people) lack access to electricity, and many more rely on poor quality electricity services. The majority of those without access (87%) reside in rural areas. This paper presents results of a geographic information systems approach coupled with open access data. We present least-cost electrification strategies on a country-by-country basis for Sub-Saharan Africa. The electrification options include grid extension, mini-grid and stand-alone systems for rural, peri-urban, and urban contexts across the economy. At low levels of electricity demand there is a strong penetration of standalone technologies. However, higher electricity demand levels move the favourable electrification option from stand-alone systems to mini grid and to grid extensions.

In sub-Saharan Africa (SSA), tropical dry forests and savannas cover over 2.5 million km² and support livelihoods for millions in fast-growing nations. Intensifying land use pressures have driven rapid changes in tree cover structure (basal area, biomass) that remain poorly characterized at regional scales. Here, we posed the hypothesis that tree cover structure related strongly to senesced and non-photosynthetic (NPV) vegetation features in a SSA tropical dry forest landscape, offering improved means for satellite remote sensing of tree cover structure compared to vegetation greenness-based methods. Across regrowth miombo woodland sites in Tanzania, we analyzed relationships among field data on tree structure, land cover, and satellite indices of green and NPV features based on spectral mixture analyses and normalized difference vegetation index calculated from Landsat 8 data. From satellite-field data relationships, we mapped regional basal area and biomass using NPV and greenness-based metrics, and compared map performances at landscape scales. Total canopy cover related significantly to stem basal area (r² = 0.815, p < 0.01) and biomass (r² = 0.635, p < 0.01), and NPV dominated ground cover (> 60%) at all sites. From these two conditions emerged a key inverse relationship: skyward exposure of NPV ground cover was high at sites with low tree basal area and biomass, and decreased with increasing stem basal area and biomass. This pattern scaled to Landsat NPV metrics, which showed strong inverse correlations to basal area (Pearson r = −0.85, p < 0.01) and biomass (r = −0.86, p < 0.01). Biomass estimates from Landsat NPV-based maps matched field data, and significantly differentiated landscape gradients in woody biomass that greenness metrics failed to track. The results suggest senesced vegetation metrics at Landsat scales are a promising means for improved monitoring of tree structure across disturbance and ecological gradients in African and other tropical dry forests.

In rapidly urbanizing semi-arid regions, increasing amounts of historically irrigated cropland lies permanently fallowed due to water court policies as agricultural water rights are voluntarily being sold to growing cities. This study develops an integrative framework for assessing the effects of population growth and land use change on agricultural production and evaluating viability of alternative management strategies, including alternative agricultural transfer methods, regional water ownership restrictions, and urban conservation. A partial equilibrium model of a spatially-diverse regional water rights market is built in application of the framework to an exemplary basin. The model represents agricultural producers as profit-maximizing suppliers and municipalities as cost-minimizing consumers of water rights. Results indicate that selling an agricultural water right today is worth up to two times more than 40 years of continued production. All alternative policies that sustain agricultural cropland and crop production decrease total agricultural profitability by diminishing water rights sales revenue, but in doing so, they also decrease municipal water acquisition costs. Defining good indicators and incorporating adequate spatial and temporal detail are critical to properly analyzing policy impacts. To best improve agricultural profit from production and sale of crops, short-term solutions include alternative agricultural transfer methods while long-term solutions incorporate urban conservation.

In this study, we estimate rice residue, associated burning emissions, and compare results with existing emissions inventories employing a bottom-up approach. We first estimated field-level post-harvest rice residues, including separate fuel-loading factors for rice straw and rice stubble. Results suggested fuel-loading factors of 0.27 kg m⁻² (±0.033), 0.61 kg m⁻² (±0.076), and 0.88 kg m⁻² (±0.083) for rice straw, stubble, and total post-harvest biomass, respectively. Using these factors, we quantified potential emissions from rice residue burning and compared our estimates with other studies. Our results suggest total rice residue burning emissions as 2.24 Gg PM_2.5, 36.54 Gg CO and 567.79 Gg CO₂ for Hanoi Province, which are significantly higher than earlier studies. We attribute our higher emission estimates to improved fuel-loading factors; moreover, we infer that some earlier studies relying on residue-to-product ratios could be underestimating rice residue emissions by more than a factor of 2.3 for Hanoi, Vietnam. Using the rice planted area data from the Vietnamese government, and combining our fuel-loading factors, we also estimated rice residue PM_2.5 emissions for the entirety of Vietnam and compared these estimates with an existing all-sources emissions inventory, and the Global Fire Emissions Database (GFED). Results suggest 75.98 Gg of PM_2.5 released from rice residue burning accounting for 12.8% of total emissions for Vietnam. The GFED database suggests 42.56 Gg PM_2.5 from biomass burning with 5.62 Gg attributed to agricultural waste burning indicating satellite-based methods may be significantly underestimating emissions. Our results not only provide improved residue and emission estimates, but also highlight the need for emissions mitigation from rice residue burning.

Woody shrubs have increased in biomass and expanded into new areas throughout the Pan-Arctic tundra biome in recent decades, which has been linked to a biome-wide observed increase in productivity. Experimental, observational, and socio-ecological research suggests that air temperature—and to a lesser degree precipitation—trends have been the predominant drivers of this change. However, a progressive decoupling of these drivers from Arctic vegetation productivity has been reported, and since 2010, vegetation productivity has also been declining. We created a protocol to (a) identify the suite of controls that may be operating on shrub growth and expansion, and (b) characterise the evidence base for controls on Arctic shrub growth and expansion. We found evidence for a suite of 23 proximal controls that operate directly on shrub growth and expansion; the evidence base focused predominantly on just four controls (air temperature, soil moisture, herbivory, and snow dynamics). 65% of evidence was generated in the warmest tundra climes, while 24% was from only one of 28 floristic sectors. Temporal limitations beyond 10 years existed for most controls, while the use of space-for-time approaches was high, with 14% of the evidence derived via experimental approaches. The findings suggest the current evidence base is not sufficiently robust or comprehensive at present to answer key questions of Pan-Arctic shrub change. We suggest future directions that could strengthen the evidence, and lead to an understanding of the key mechanisms driving changes in Arctic shrub environments.

An error in the unit conversion from pixels to hectares lead to all the areal quantities in the text being smaller than they should have been. Only the number of hectares were changed; none of the text nor tables were changed. The changes do not affect the overall results or conclusions.