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Warmer conditions over the past two decades have contributed to rapid expansion of bark beetle outbreaks killing millions of trees over a large fraction of western United States (US) forests. These outbreaks reduce plant productivity by killing trees and transfer carbon from live to dead pools where carbon is slowly emitted to the atmosphere via heterotrophic respiration which subsequently feeds back to climate change. Recent studies have begun to examine the local impacts of bark beetle outbreaks in individual stands, but the full regional carbon consequences remain undocumented for the western US. In this study, we quantify the regional carbon impacts of the bark beetle outbreaks taking place in western US forests. The work relies on a combination of postdisturbance forest regrowth trajectories derived from forest inventory data and a process-based carbon cycle model tracking decomposition, as well as aerial detection survey (ADS) data documenting the regional extent and severity of recent outbreaks. We find that biomass killed by bark beetle attacks across beetle-affected areas in western US forests from 2000 to 2009 ranges from 5 to 15 Tg C yr(-1) and caused a reduction of net ecosystem productivity (NEP) of about 6.1-9.3 Tg C y(-1) by 2009. Uncertainties result largely from a lack of detailed surveys of the extent and severity of outbreaks, calling out a need for improved characterization across western US forests. The carbon flux legacy of 2000-2009 outbreaks will continue decades into the future (e.g., 2040-2060) as committed emissions from heterotrophic respiration of beetle-killed biomass are balanced by forest regrowth and accumulation.

Climate change and increased anthropogenic activities are expected to elevate the potential of introducing nonindigenous species (NIS) into the Arctic. Yet, the knowledge base needed to identify gaps and priorities for NIS research and management is limited. Here, we reviewed primary introduction events to each ecoregion of the marine Arctic realm to identify temporal and spatial patterns, likely source regions of NIS, and the putative introduction pathways. We included 54 introduction events representing 34 unique NIS. The rate of NIS discovery ranged from zero to four species per year between 1960 and 2015. The Iceland Shelf had the greatest number of introduction events (n = 14), followed by the Barents Sea (n = 11), and the Norwegian Sea (n = 11). Sixteen of the 54 introduction records had no known origins. The majority of those with known source regions were attributed to the Northeast Atlantic and the Northwest Pacific, 19 and 14 records, respectively. Some introduction events were attributed to multiple possible pathways. For these introductions, vessels transferred the greatest number of aquatic NIS (39%) to the Arctic, followed by natural spread (30%) and aquaculture activities (25%). Similar trends were found for introductions attributed to a single pathway. The phyla Arthropoda and Ochrophyta had the highest number of recorded introduction events, with 19 and 12 records, respectively. Recommendations including vector management, horizon scanning, early detection, rapid response, and a pan‐Arctic biodiversity inventory are considered in this paper. Our study provides a comprehensive record of primary introductions of NIS for marine environments in the circumpolar Arctic and identifies knowledge gaps and opportunities for NIS research and management. Ecosystems worldwide will face dramatic changes in the coming decades due to global change. Our findings contribute to the knowledge base needed to address two aspects of global change—invasive species and climate change., This paper examines the current status and future risks of biological invasions in the marine environments of the Arctic, within the context of climate change, natural resource development, and expanded Arctic shipping. The number of nonindigenous species introductions varied across the region with the greatest number of introductions recorded in the Iceland Shelf, followed by the Barents Sea and the Norwegian Sea. Most introductions were attributed to vessels, natural spread, and aquaculture activities. Vector management, horizon scanning, early detection, rapid response, and a pan‐Arctic biodiversity inventory are recommended to address future invasion risks.

Nitrous oxide (N2O) is a powerful greenhouse gas. The UK government is committed to reducing all greenhouse gas emissions and is required to make an inventory of the sources and emissions of these gases. Here, we extend work from a pilot study at the catchment scale reported in an earlier paper. This paper reports on the upscaling measurements of emissions to derive annual emission rates for specific combinations of soil type, land management and fertiliser practices to the national scale. Digital soil, climate and land use maps were combined within Geographic Information Systems (GIS) software. Upscaling of field emissions measurements involves adjusting measured annual N2O emissions to fit combinations of crop growth cycles, soil wetness and the amount and timing of fertiliser applications. We have also taken account of the differences in emission rates from grazed pasture land due to differences in land management between land utilised for dairy production and land utilised for beef production. Calculated annual emission rates were then spatially scaled to derive national figures through the use of a GIS modelling framework, termed NitOx. The annual emission of N2O from Scotland was determined as approximately 6 000 000 kg N yr−1 (2.8 Mt carbon dioxide (CO2) equivalents) and compares favourably with other national scale estimates such as the IPCC (1997). The combination of animal grazing, high N inputs, climatic warmth and poorly drained soils means that the south west contributes significantly to the national total N2O emissions. Localised areas of high emission can also be identified, but identification could be improved by applying this modelling approach at a larger scale. It would be beneficial to target these areas with mitigation strategies.

Changes to forest production drivers (light, water, temperature, and site nutrient) over the last 55 years have been documented in peer-reviewed literature. The main objective of this paper is to review documented evidence of the impacts of climate change trends on forest productivity since the middle of the 20th century. We first present a concise overview of the climate controls of forest production, provide evidence of how the main controls have changed in the last 55 years, followed by a core section outlining our findings of observed and documented impacts on forest productivity and a brief discussion of the complications of interpreting trends in net primary production (NPP). At finer spatial scales, a trend is difficult to decipher, but globally, based on both satellite and ground-based data, climatic changes seemed to have a generally positive impact on forest productivity when water was not limiting. Of the 49 papers reporting forest production levels we reviewed, 37 showed a positive growth trend, five a negative trend, three reported both a positive and a negative trend for different time periods, one reported a positive and no trend for different geographic areas, and two reported no trend. Forests occupy 52% of the Earth’s land surface and tend to occupy more temperature and radiation-limited environments. Less than 7% of forests are in strongly water-limited systems. The combined and interacting effects of temperature, radiation, and precipitation changes with the positive effect of CO2, the negative effects of O3 and other pollutants, and the presently positive effects of N will not be elucidated with experimental manipulation of one or a few factors at a time. Assessments of the greening of the biosphere depend on both accurate measurements of rates (net ecosystem exchange, NPP), how much is stored at the ecosystem level (net ecosystem production) and quantification of disturbances rates on final net biome production.

The Amazon River, its huge basin, and the changes in biological processes that are rapidly occurring in this region are unquestionably of global significance. Hence, Global Change Biology is delighted to host a special thematic issue devoted to the Large-scale Biosphere–Atmosphere Experiment in Amazonia (LBA), which is a multinational, interdisciplinary research program led by Brazil. The goal of LBA is no less modest than its subject: to understand how Amazonia functions as a regional entity in the Earth system and how these functions are changing as a result of ongoing changes in land use. This compilation of 26 papers resulting from LBA-related research covers a broad range of topics: forest stocks of carbon (C) and nitrogen (N); fluxes of greenhouse gases and volatile organic compounds from vegetation, soils and wetlands; mapping and modeling land-use change, fire risk, and soil properties; measuring changes caused by logging, pasturing and cultivating; and new research approaches in meteorology to estimate nocturnal fluxes of C from forests and pastures. Some important new synthesis can be derived from these and other studies. The aboveground biomass of intact Amazonian forests appears to be a sink for atmospheric carbon dioxide (CO2), while the wetlands and soils are a net source of atmospheric methane (CH4) and nitrous oxide (N2O), respectively. Land-use change has, so far, had only a minor effect on basin-wide emissions of CH4 and N2O, but the net effect of deforestation and reforestation appears to be a significant net release of CO2 to the atmosphere. The sum of the 100-year global warming potentials (GWP) of these annual sources and sinks of CH4, N2O, and CO2 indicate that the Amazonian forest–river system currently may be nearly balanced in terms of the net GWP of these biogenic atmospheric gases. Of course, large uncertainties remain for these estimates, but the papers published here demonstrate tremendous progress, and also large remaining hurdles, in narrowing these uncertainties in our understanding of how Amazonia functions as a regional entity in the Earth system.

Hydrologists and ecologists studying tundra ecosystems have worked largely independently, with little cross-fertilization between disciplines. Their disciplines are, however, inextricably linked by a need to understand the dynamics and significance of the common substance water, in its liquid, solid and gaseous state within tundra environments. The impacts of predicted long-term changes in climate have particularly important consequences for the functioning of tundra systems and there is a pressing need to initiate studies that integrate hydrological and ecological methodologies and concepts. Our paper attempts to summarize existing information on the role of water within tundra ecosystems, to emphasize the fundamental links between the biotic and the physico/chemical environments and to suggest how a closer integration of ideas might be achieved. Given the breadth of the subject matter the paper is intended to be illustrative rather than comprehensive. The paper examines the physical impacts of water in its various states on the tundra environment, emphasizing in particular the causes of spatial variation in water availability to living organisms. The significance of water is discussed for a range of organism groups, including plants, invertebrates and microorganisms and its pivotal role in ecosystem function and disturbance stressed. The need to develop integrated hydological/ecological models for tundra systems on different spatial scales is emphasized.

The International Tundra Experiment (ITEX) was established in late 1990 at a meeting of arctic tundra ecologists as a response to predictions that the human-enhanced greenhouse warming would occur earliest and most intensely at high latitudes. The initial objective of ITEX was to monitor phenology, growth and reproduction in major circumpolar vascular plant species in response to climate variations and environmental manipulations at sites throughout the tundra biome. The manipulations involve passive warming of tundra plots in open-top chambers (OTCs), and manipulating snow depth to alter growing season length. Standard protocols were developed for measurements, experimental design and statistical analyses, and published in an ITEX Manual. The standard methods ensure comparable data are collected at all sites. This special issue of Global Change Biology is based on papers developed from the 6th ITEX Workshop, held at the University of Ottawa, Ottawa, Canada, 7–11 April 1995. The papers compare short-term responses (1–3 years) of common species to climate variations and manipulations at ITEX sites. The OTCs increase mean near-surface temperatures by 1–3°C during the growing season, simulating predictions from global circulation models. All species investigated responded to the temperature increase, especially in phenology and reproductive variables. However, these short-term responses were individualistic, and no general pattern in type or magnitude of response was noted for functional types or phenology class. Responses were generally similar among sites, although the magnitude of response tended to be greater in high Arctic sites. Early snowmelt increased carbon:nutrient ratios in plants. Sustained growth and reproductive responses to warming will depend on nutrient supply, and increased carbon:nutrient ratios in litter could buffer nutrient cycling, and hence plant growth. Ongoing, long-term research at ITEX sites, linked to other global change initiatives, will help elucidate probable effects of climate change at the ecosystems level in arctic and alpine tundra.

The terrestrial biosphere plays an important role in the global carbon cycle. In the 1994 Intergovernmental Panel Assessment on Climate Change (IPCC), an effort was made to improve the quantification of terrestrial exchanges and potential feedbacks from climate, changing CO2, and other factors; this paper presents the key results from that assessment, together with expanded discussion. The carbon cycle is the fluxes of carbon among four main reservoirs: fossil carbon, the atmosphere, the oceans, and the terrestrial biosphere. Emissions of fossil carbon during the 1980s averaged 5.5 Gt y−1. During the same period, the atmosphere gained 3.2 Gt C y−1 and the oceans are believed to have absorbed 2.0 Gt C y−1. The regrowing forests of the Northern Hemisphere may have absorbed 0.5 Gt C y−1 during this period. Meanwhile, tropical deforestation is thought to have released an average 1.6 Gt C y−1 over the 1980s. While the fluxes among the four pools should balance, the average 198Ds values lead to a ‘missing sink’ of 1.4 Gt C y−1 Several processes, including forest regrowth, CO2 fertilization of plant growth (c. 1.0 Gt C y−1), N deposition (c. 0.6 Gt C y−1), and their interactions, may account for the budget imbalance. However, it remains difficult to quantify the influences of these separate but interactive processes. Uncertainties in the individual numbers are large, and are themselves poorly quantified. This paper presents detail beyond the IPCC assessment on procedures used to approximate the flux uncertainties. Lack of knowledge about positive and negative feedbacks from the biosphere is a major limiting factor to credible simulations of future atmospheric CO2 concentrations. Analyses of the atmospheric gradients of CO2 and 13 CO2 concentrations provide increasingly strong evidence for terrestrial sinks, potentially distributed between Northern Hemisphere and tropical regions, but conclusive detection in direct biomass and soil measurements remains elusive. Current regional-to-global terrestrial ecosystem models with coupled carbon and nitrogen cycles represent the effects of CO2 fertilization differently, but all suggest longterm responses to CO2 that are substantially smaller than potential leaf- or laboratory whole plant-level responses. Analyses of emissions and biogeochemical fluxes consistent with eventual stabilization of atmospheric CO2 concentrations are sensitive to the way in which biospheric feedbacks are modeled by c. 15%. Decisions about land use can have effects of 100s of Gt C over the next few centuries, with similarly significant effects on the atmosphere. Critical areas for future research are continued measurements and analyses of atmospheric data (CO2 and 13CO2) to serve as large-scale constraints, process studies of the scaling from the photosynthetic response to CO2 to whole-ecosystem carbon storage, and rigorous quantification of the effects of changing land use on carbon storage.

The Global Carbon Project (GCP) has published global carbon budgets annually since 2007 (Canadell et al. [2007], Proc Natl Acad Sci USA, 104, 18866-18870; Raupach et al. [2007], Proc Natl Acad Sci USA, 104, 10288-10293). There are many scientists involved, but the terrestrial fluxes that appear in the budgets are not well understood by ecologists and biogeochemists outside of that community. The purpose of this paper is to make the terrestrial fluxes of carbon in those budgets more accessible to a broader community. The GCP budget is composed of annual perturbations from pre-industrial conditions, driven by addition of carbon to the system from combustion of fossil fuels and by transfers of carbon from land to the atmosphere as a result of land use. The budget includes a term for each of the major fluxes of carbon (fossil fuels, oceans, land) as well as the rate of carbon accumulation in the atmosphere. Land is represented by two terms: one resulting from direct anthropogenic effects (Land Use, Land-Use Change, and Forestry or land management) and one resulting from indirect anthropogenic (e.g., CO2 , climate change) and natural effects. Each of these two net terrestrial fluxes of carbon, in turn, is composed of opposing gross emissions and removals (e.g., deforestation and forest regrowth). Although the GCP budgets have focused on the two net terrestrial fluxes, they have paid little attention to the gross components, which are important for a number of reasons, including understanding the potential for land management to remove CO2 from the atmosphere and understanding the processes responsible for the sink for carbon on land. In contrast to the net fluxes of carbon, which are constrained by the global carbon budget, the gross fluxes are largely unconstrained, suggesting that there is more uncertainty than commonly believed about how terrestrial carbon emissions will respond to future fossil fuel emissions and a changing climate.

A paper published in Global Change Biology in 2006 revealed that phenological responses in 1971-2000 matched the warming pattern in Europe, but a lack of chilling and adaptation in farming may have reversed these findings. Therefore, for 1951-2018 in a corresponding data set, we determined changes as linear trends and analysed their variation by plant traits/groups, across season and time as well as their attribution to warming following IPCC methodology. Although spring and summer phases in wild plants advanced less (maximum advances in 1978-2007), more (~90%) and more significant (~60%) negative trends were present, being stronger in early spring, at higher elevations, but smaller for nonwoody insect-pollinated species. These trends were strongly attributable to winter and spring warming. Findings for crop spring phases were similar, but were less pronounced. There were clearer and attributable signs for a delayed senescence in response to winter and spring warming. These changes resulted in a longer growing season, but a constant generative period in wild plants and a shortened one in agricultural crops. Phenology determined by farmers' decisions differed noticeably from the purely climatic driven phases with smaller percentages of advancing (~75%) trends, but farmers' spring activities were the only group with reinforced advancement, suggesting adaptation. Trends in farmers' spring and summer activities were very likely/likely associated with the warming pattern. In contrast, the advance in autumn farming phases was significantly associated with below average summer warming. Thus, under ongoing climate change with decreased chilling the advancing phenology in spring and summer is still attributable to warming; even the farmers' activities in these seasons mirror, to a lesser extent, the warming. Our findings point to adaptation to climate change in agriculture and reveal diverse implications for terrestrial ecosystems; the strong attribution supports the necessary mediation of warming impacts to the general public.

Climate change is outpacing the ability of species and populations to naturally adapt warranting active interventions to boost climate resilience. In their review paper, Gaitán-Espitia and Hobday discuss how such interventions may, however, counter natural evolutionary processes and adaptive capacity if not underpinned by background knowledge from genes through to ecosystems. They present a robust decision framework to guide implementation of climate adaptation interventions to avoid unintended evolutionary outcomes.

Due to their position at the land-sea interface, barrier islands are vulnerable to both oceanic and atmospheric climate change-related drivers. In response to relative sea-level rise, barrier islands tend to migrate landward via overwash processes which deposit sediment onto the backbarrier marsh, thus maintaining elevation above sea level. In this paper, we assess the importance of interior upland vegetation and sediment transport (from upland to marsh) on the movement of the marsh-upland boundary in a transgressive barrier system along the mid-Atlantic Coast. We hypothesize that recent woody expansion is altering the rate of marsh to upland conversion. Using Landsat imagery over a 32 year time period (1984-2016), we quantify transitions between land cover (bare, grassland, woody vegetation, and marsh) and the marsh-upland boundary. We find that the Virginia Barrier Islands have both gains and losses in backbarrier marsh and upland, with 19% net loss from the system during the timeframe of the study and increased variance in marsh to upland conversion. This is consistent with recent work indicating a shift toward increasing rates of landward barrier island migration. Despite a net loss of upland area, macroclimatic winter warming resulted in 41% increase in woody vegetation in protected, low-elevation areas, introducing new ecological scenarios that increase resistance to sediment movement from upland to marsh. Our analysis demonstrates how the interplay between elevation and interior island vegetative cover influences landward migration of the boundary between upland and marsh (a previously underappreciated indicator that an island is migrating), and thus, the importance of including ecological processes in the island interior into coastal modeling of barrier island migration and sediment movement across the barrier landscape.

Farmers are carving a new agricultural frontier from the forests in the Southeast Asian Massif (SAM) in the 21st century, triggering significant environment degradation at the local scale; however, this frontier has been missed by existing global land use and forest loss analyses. In this paper, we chose Thailand's Nan Province, which is located in the geometric center of SAM, as a case study, and combined high resolution forest cover change product with a fine-scale land cover map to investigate land use dynamics with respect to topography in this region. Our results show that total forest loss in Nan Province during 2001-2016 was 66,072 ha (9.1% of the forest cover in 2000), and that the majority of this lost forest (92%) had been converted into crop (mainly corn) fields by 2017. Annual forest loss is significantly correlated with global corn price (p < 0.01), re-confirming agricultural expansion as a key driver of forest loss in Nan Province. Along with the increasing global corn price, forest loss in Nan Province has accelerated at a rate of 2,616 ± 730 ha per decade (p < 0.01). Global corn price peaked in 2012, in which year annual forest loss also reached its peak (7,523 ha); since then, the location of forest loss has moved to steeper land at higher elevations. Spatially, forest loss driven by this smallholder agricultural expansion emerges as many small patches that are not recognizable even at a moderate spatial resolution (e.g. 300 m). It explains how existing global land use/cover change products have missed the widespread and rapid forest loss in SAM. It also highlights the importance of high-resolution observations to evaluate the environmental impacts of agricultural expansion and forest loss in SAM, including, but not limited to, the impacts on the global carbon cycle, regional hydrology, and local environmental degradation.

Information on the response of vegetation to different environmental drivers, including rainfall, forms a critical input to ecosystem models. Currently, such models are run based on parameters that, in some cases, are either assumed or lack supporting evidence (e.g., that vegetation growth across Africa is rainfall-driven). A limited number of studies have reported that the onset of rain across Africa does not fully explain the onset of vegetation growth, for example, drawing on the observation of prerain flush effects in some parts of Africa. The spatial extent of this prerain green-up effect, however, remains unknown, leaving a large gap in our understanding that may bias ecosystem modelling. This paper provides the most comprehensive spatial assessment to-date of the magnitude and frequency of the different patterns of phenology response to rainfall across Africa and for different vegetation types. To define the relations between phenology and rainfall, we investigated the spatial variation in the difference, in number of days, between the start of rainy season (SRS) and start of vegetation growing season (SOS); and between the end of rainy season (ERS) and end of vegetation growing season (EOS). We reveal a much more extensive spread of prerain green-up over Africa than previously reported, with prerain green-up being the norm rather than the exception. We also show the relative sparsity of postrain green-up, confined largely to the Sudano-Sahel region. While the prerain green-up phenomenon is well documented, its large spatial extent was not anticipated. Our results, thus, contrast with the widely held view that rainfall drives the onset and end of the vegetation growing season across Africa. Our findings point to a much more nuanced role of rainfall in Africa's vegetation growth cycle than previously thought, specifically as one of a set of several drivers, with important implications for ecosystem modelling.

Salinity intrusion caused by land subsidence resulting from increasing groundwater abstraction, decreasing river sediment loads and increasing sea level because of climate change has caused widespread soil salinization in coastal ecosystems. Soil salinization may greatly alter nitrogen (N) cycling in coastal ecosystems. However, a comprehensive understanding of the effects of soil salinization on ecosystem N pools, cycling processes and fluxes is not available for coastal ecosystems. Therefore, we compiled data from 551 observations from 21 peer-reviewed papers and conducted a meta-analysis of experimental soil salinization effects on 19 variables related to N pools, cycling processes and fluxes in coastal ecosystems. Our results showed that the effects of soil salinization varied across different ecosystem types and salinity levels. Soil salinization increased plant N content (18%), soil NH4+ (12%) and soil total N (210%), although it decreased soil NO3− (2%) and soil microbial biomass N (74%). Increasing soil salinity stimulated soil N2O fluxes as well as hydrological NH4+ and NO2− fluxes more than threefold, although it decreased the hydrological dissolved organic nitrogen (DON) flux (59%). Soil salinization also increased the net N mineralization by 70%, although salinization effects were not observed on the net nitrification, denitrification and dissimilatory nitrate reduction to ammonium in this meta-analysis. Overall, this meta-analysis improves our understanding of the responses of ecosystem N cycling to soil salinization, identifies knowledge gaps and highlights the urgent need for studies on the effects of soil salinization on coastal agro-ecosystem and microbial N immobilization. Additional increases in knowledge are critical for designing sustainable adaptation measures to the predicted intrusion of salinity intrusion so that the productivity of coastal agro-ecosystems can be maintained or improved and the N losses and pollution of the natural environment can be minimized.

Despite 20 years of effort to curb emissions, greenhouse gas (GHG) emissions grew faster during the 2000s than in the 1990s, which presents a major challenge for meeting the international goal of limiting warming to2 °C relative to the preindustrial era. Most recent scenarios from integrated assessment models require large-scale deployment of negative emissions technologies (NETs) to reach the 2 °C target. A recent analysis of NETs, including direct air capture, enhanced weathering, bioenergy with carbon capture and storage and afforestation/deforestation, showed that all NETs have significant limits to implementation, including economic cost, energy requirements, land use, and water use. In this paper, I assess the potential for negative emissions from soil carbon sequestration and biochar addition to land, and also the potential global impacts on land use, water, nutrients, albedo, energy and cost. Results indicate that soil carbon sequestration and biochar have useful negative emission potential (each 0.7 GtCeq. yr(-1) ) and that they potentially have lower impact on land, water use, nutrients, albedo, energy requirement and cost, so have fewer disadvantages than many NETs. Limitations of soil carbon sequestration as a NET centre around issues of sink saturation and reversibility. Biochar could be implemented in combination with bioenergy with carbon capture and storage. Current integrated assessment models do not represent soil carbon sequestration or biochar. Given the negative emission potential of SCS and biochar and their potential advantages compared to other NETs, efforts should be made to include these options within IAMs, so that their potential can be explored further in comparison with other NETs for climate stabilization.

The accelerating rate of global change has focused attention on the cumulative impacts of novel and extreme environmental changes (i.e. stressors), especially in marine ecosystems. As integrators of local catchment and regional processes, freshwater ecosystems are also ranked highly sensitive to the net effects of multiple stressors, yet there has not been a large-scale quantitative synthesis. We analysed data from 88 papers including 286 responses of freshwater ecosystems to paired stressors and discovered that overall, their cumulative mean effect size was less than the sum of their single effects (i.e. an antagonistic interaction). Net effects of dual stressors on diversity and functional performance response metrics were additive and antagonistic, respectively. Across individual studies, a simple vote-counting method revealed that the net effects of stressor pairs were frequently more antagonistic (41%) than synergistic (28%), additive (16%) or reversed (15%). Here, we define a reversal as occurring when the net impact of two stressors is in the opposite direction (negative or positive) from that of the sum of their single effects. While warming paired with nutrification resulted in additive net effects, the overall mean net effect of warming combined with a second stressor was antagonistic. Most importantly, the mean net effects across all stressor pairs and response metrics were consistently antagonistic or additive, contrasting the greater prevalence of reported synergies in marine systems. Here, a possible explanation for more antagonistic responses by freshwater biota to stressors is that the inherent greater environmental variability of smaller aquatic ecosystems fosters greater potential for acclimation and co-adaptation to multiple stressors.

The need for rigorous analyses of climate impacts has never been more crucial. Current textbooks state that climate directly influences ecosystem annual net primary productivity (NPP), emphasizing the urgent need to monitor the impacts of climate change. A recent paper challenged this consensus, arguing, based on an analysis of NPP for 1247 woody plant communities across global climate gradients, that temperature and precipitation have negligible direct effects on NPP and only perhaps have indirect effects by constraining total stand biomass (Mtot ) and stand age (a). The authors of that study concluded that the length of the growing season (lgs ) might have a minor influence on NPP, an effect they considered not to be directly related to climate. In this article, we describe flaws that affected that study's conclusions and present novel analyses to disentangle the effects of stand variables and climate in determining NPP. We re-analyzed the same database to partition the direct and indirect effects of climate on NPP, using three approaches: maximum-likelihood model selection, independent-effects analysis, and structural equation modeling. These new analyses showed that about half of the global variation in NPP could be explained by Mtot combined with climate variables and supported strong and direct influences of climate independently of Mtot , both for NPP and for net biomass change averaged across the known lifetime of the stands (ABC = average biomass change). We show that lgs is an important climate variable, intrinsically correlated with, and contributing to mean annual temperature and precipitation (Tann and Pann ), all important climatic drivers of NPP. Our analyses provide guidance for statistical and mechanistic analyses of climate drivers of ecosystem processes for predictive modeling and provide novel evidence supporting the strong, direct role of climate in determining vegetation productivity at the global scale.

Arabica coffee (Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. Published studies show that climate change is projected to have a substantial negative influence on the current suitable growing areas for indigenous Arabica in Ethiopia and South Sudan. Here we use all available future projections for the species based on multiple general circulation models (GCMs), emission scenarios, and migration scenarios, to predict changes in Extent of Occurrence (EOO), Area of Occupancy (AOO), and population numbers for wild Arabica coffee. Under climate change our results show that population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. EOO and AOO are projected to decline by around 30% in many cases. Furthermore, present‐day models compared to the near future (2038), show a reduction for EOO of over 40% (with a few cases over 50%), although EOO should be treated with caution due to its sensitivity to outlying occurrences. When applying these metrics to extinction risk, we show that the determination of generation length is critical. When applying the International Union for Conservation of Nature's Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (not threatened) when applying the IUCN Red List criteria., Arabica coffee (Coffea arabica) is a key crop in many tropical countries and globally provides an export value of over US$13 billion per year. Wild Arabica coffee is of fundamental importance for the global coffee sector and of direct importance within Ethiopia, as a source of harvestable income and planting stock. In this paper we show that under climate change alone, population numbers could reduce by 50% or more (with a few models showing over 80%) by 2088. When applying the International Union for Conservation of Nature’s Red list of Threatened Species (IUCN Red List) criteria, even with a very conservative generation length of 21 years, wild Arabica coffee is assessed as Threatened with extinction (placed in the Endangered category) under a broad range of climate change projections, if no interventions are made. Importantly, if we do not include climate change in our assessment, Arabica coffee is assessed as Least Concern (not threatened) when applying the IUCN Red List criteria.

The effects of anthropogenic global environmental change on biotic and abiotic processes have been reported in aquatic systems across the world. Complex synergies between concurrent environmental stressors and the resilience of the system to regime shifts, which vary in space and time, determine the capacity for marine systems to maintain structure and function with global environmental change. Consequently, an interdisciplinary approach that facilitates the development of new methods for the exchange of knowledge between scientists across multiple scales is required to effectively understand, quantify and predict climate impacts on marine ecosystem services. We use a literature review to assess the limitations and assumptions of current pathways to exchange interdisciplinary knowledge and the transferability of research findings across spatial and temporal scales and levels of biological organization to advance scientific understanding of global environmental change in marine systems. We found that species-specific regional scale climate change research is most commonly published, and "supporting" is the ecosystem service most commonly referred to in publications. In addition, our paper outlines a trajectory for the future development of integrated climate change science for sustaining marine ecosystem services such as investment in interdisciplinary education and connectivity between disciplines.

Terrestrial ecosystems sequester roughly 30% of anthropogenic carbon emission. However this estimate has not been directly deduced from studies of terrestrial ecosystems themselves, but inferred from atmospheric and oceanic data. This raises a question: to what extent is the terrestrial carbon cycle intrinsically predictable? In this paper, we investigated fundamental properties of the terrestrial carbon cycle, examined its intrinsic predictability, and proposed a suite of future research directions to improve empirical understanding and model predictive ability. Specifically, we isolated endogenous internal processes of the terrestrial carbon cycle from exogenous forcing variables. The internal processes share five fundamental properties (i.e., compartmentalization, carbon input through photosynthesis, partitioning among pools, donor pool-dominant transfers, and the first-order decay) among all types of ecosystems on the Earth. The five properties together result in an emergent constraint on predictability of various carbon cycle components in response to five classes of exogenous forcing. Future observational and experimental research should be focused on those less predictive components while modeling research needs to improve model predictive ability for those highly predictive components. We argue that an understanding of predictability should provide guidance on future observational, experimental and modeling research.

Quantifying global soil respiration (RSG ) and its response to temperature change are critical for predicting the turnover of terrestrial carbon stocks and their feedbacks to climate change. Currently, estimates of RSG range from 68 to 98 Pg C year-1 , causing considerable uncertainty in the global carbon budget. We argue the source of this variability lies in the upscaling assumptions regarding the model format, data timescales, and precipitation component. To quantify the variability and constrain RSG , we developed RSG models using Random Forest and exponential models, and used different timescales (daily, monthly, and annual) of soil respiration (RS ) and climate data to predict RSG . From the resulting RSG estimates (range = 66.62-100.72 Pg), we calculated variability associated with each assumption. Among model formats, using monthly RS data rather than annual data decreased RSG by 7.43-9.46 Pg; however, RSG calculated from daily RS data was only 1.83 Pg lower than the RSG from monthly data. Using mean annual precipitation and temperature data instead of monthly data caused +4.84 and -4.36 Pg C differences, respectively. If the timescale of RS data is constant, RSG estimated by the first-order exponential (93.2 Pg) was greater than the Random Forest (78.76 Pg) or second-order exponential (76.18 Pg) estimates. These results highlight the importance of variation at subannual timescales for upscaling to RSG . The results indicated RSG is lower than in recent papers and the current benchmark for land models (98 Pg C year-1 ), and thus may change the predicted rates of terrestrial carbon turnover and the carbon to climate feedback as global temperatures rise.

Food security and agriculture productivity assessments in sub-Saharan Africa (SSA) require a better understanding of how climate and other drivers influence regional crop yields. In this paper, our objective was to identify the climate signal in the realized yields of maize, sorghum, and groundnut in SSA. We explored the relation between crop yields and scale-compatible climate data for the 1962-2014 period using Random Forest, a diagnostic machine learning technique. We found that improved agricultural technology and country fixed effects are three times more important than climate variables for explaining changes in crop yields in SSA. We also found that increasing temperatures reduced yields for all three crops in the temperature range observed in SSA, while precipitation increased yields up to a level roughly matching crop evapotranspiration. Crop yields exhibited both linear and nonlinear responses to temperature and precipitation, respectively. For maize, technology steadily increased yields by about 1% (13 kg/ha) per year while increasing temperatures decreased yields by 0.8% (10 kg/ha) per °C. This study demonstrates that although we should expect increases in future crop yields due to improving technology, the potential yields could be progressively reduced due to warmer and drier climates.

The establishment of either forest or grassland on degraded cropland has been proposed as an effective method for climate change mitigation because these land use types can increase soil carbon (C) stocks. This paper synthesized 135 recent publications (844 observations at 181 sites) focused on the conversion from cropland to grassland, shrubland or forest in China, better known as the 'Grain-for-Green' Program to determine which factors were driving changes to soil organic carbon (SOC). The results strongly indicate a positive impact of cropland conversion on soil C stocks. The temporal pattern for soil C stock changes in the 0-100 cm soil layer showed an initial decrease in soil C during the early stage (5 years), and then an increase to net C gains (5 years) coincident with vegetation restoration. The rates of soil C change were higher in the surface profile (0-20 cm) than in deeper soil (20-100 cm). Cropland converted to forest (arbor) had the additional benefit of a slower but more persistent C sequestration capacity than shrubland or grassland. Tree species played a significant role in determining the rate of change in soil C stocks (coniferbroadleaf, evergreendeciduous forests). Restoration age was the main factor, not temperature and precipitation, affecting soil C stock change after cropland conversion with higher initial soil C stock sites having a negative effect on soil C accumulation. Soil C sequestration significantly increased with restoration age over the long-term, and therefore, the large scale of land-use change under the 'Grain-for-Green' Program will significantly increase China's C stocks.

Globally, spatial distributions of fish stocks are shifting but although the role of climate change in range shifts is increasingly appreciated, little remains known of the likely additional impact that high levels of fishing pressure might have on distribution. For North Sea cod, we show for the first time and in great spatial detail how the stock has shifted its distribution over the past 100 years. We digitized extensive historical fisheries data from paper charts in UK government archives and combined these with contemporary data to a time-series spanning 1913-2012 (excluding both World Wars). New analysis of old data revealed that the current distribution pattern of cod - mostly in the deeper, northern- and north-easternmost parts of the North Sea - is almost opposite to that during most of the Twentieth Century - mainly concentrated in the west, off England and Scotland. Statistical analysis revealed that the deepening, northward shift is likely attributable to warming; however, the eastward shift is best explained by fishing pressure, suggestive of significant depletion of the stock from its previous stronghold, off the coasts of England and Scotland. These spatial patterns were confirmed for the most recent 3 1/2 decades by data from fisheries-independent surveys, which go back to the 1970s. Our results demonstrate the fundamental importance of both climate change and fishing pressure for our understanding of changing distributions of commercially exploited fish.

Climate change and habitat loss are both key threatening processes driving the global loss in biodiversity. Yet little is known about their synergistic effects on biological populations due to the complexity underlying both processes. If the combined effects of habitat loss and climate change are greater than the effects of each threat individually, current conservation management strategies may be inefficient and at worst ineffective. Therefore, there is a pressing need to identify whether interacting effects between climate change and habitat loss exist and, if so, quantify the magnitude of their impact. In this article, we present a meta-analysis of studies that quantify the effect of habitat loss on biological populations and examine whether the magnitude of these effects depends on current climatic conditions and historical rates of climate change. We examined 1319 papers on habitat loss and fragmentation, identified from the past 20 years, representing a range of taxa, landscapes, land-uses, geographic locations and climatic conditions. We find that current climate and climate change are important factors determining the negative effects of habitat loss on species density and/or diversity. The most important determinant of habitat loss and fragmentation effects, averaged across species and geographic regions, was current maximum temperature, with mean precipitation change over the last 100 years of secondary importance. Habitat loss and fragmentation effects were greatest in areas with high maximum temperatures. Conversely, they were lowest in areas where average rainfall has increased over time. To our knowledge, this is the first study to conduct a global terrestrial analysis of existing data to quantify and test for interacting effects between current climate, climatic change and habitat loss on biological populations. Understanding the synergistic effects between climate change and other threatening processes has critical implications for our ability to support and incorporate climate change adaptation measures into policy development and management response.

Increasing temperatures are likely to impact ectothermic pests of fruits and nuts. This paper aims to assess changes to pest pressure in California’s US$0.7 billion walnut industry due to recent historic and projected future temperature changes. For two past (1950 and 2000) and 18 future climate scenarios (2041–2060 and 2080–2099; each for three General Circulation Models and three greenhouse gas emissions scenarios), 100 years of hourly temperature were generated for 205 locations. Degree-day models were used to project mean generation numbers for codling moth (Cydia pomonella L.), navel orangeworm (Amyelois transitella Walker), two-spotted spider mite (Tetranychus urticae Koch), and European red mite (Panonychus ulmi Koch). In the Central Valley, the number of codling moth generations predicted for degree days accumulated between April 1 and October 1 rose from 2–4 in 1950 to 3–5 among all future scenarios. Generation numbers increased from 10–18 to 14–24 for two-spotted spider mite, from 9–14 to 14–20 for European red mite, and from 2–4 to up to 5 for navel orangeworm. Overall pest pressure can thus be expected to increase substantially. Our study did not include the possibility of higher winter survival rates, leading to higher initial pest counts in spring, or of extended pest development times in the summer, factors that are likely to exacerbate future pest pressure. On the other hand, initiation of diapause may prevent an extension of the season length for arthropods, and higher incidence of heat death in summer may constrain pest population sizes. More information on the impact of climate change on complex agroecological food webs and on the response of pests to high temperatures is needed for improving the reliability of projections.

Climate change will have substantial impacts on biodiversity, particularly for aquatic species. Warming temperatures and changing weather patterns will also remobilize and modify chemical partitioning. Holding millions of cubic yards of sediments contaminated with persistent legacy chemicals such as polychlorinated biphenyls (PCBs) and dioxins, the Laurentian Great Lakes are a laboratory for observing interactions between biological and chemical responses to climate change. They provide a wide range of habitat to a variety of species, from littoral forage fish to deep-water predators. In this paper, we couple bioenergetic and bioaccumulation models to investigate the biological and chemical effects of climate change in the Great Lakes. We consider three species: round goby, a warm-water invasive forage fish; mottled sculpin, a cool-water native forage fish; and lake trout, a cold-water native predator. Using our coupled models, we calculate the accumulation of a representative persistent chemical, PCB-77, under four climate scenarios for Lake Erie and Lake Superior. Predator-prey (lake trout-round goby) interactions and food availability (high-low) are incorporated into our simulations. For cool- to cold-water species (sculpin, lake trout) we find that warm temperatures limit growth. For warm-water species (round goby) cold temperatures limit growth. The impact of climate warming on growth depends on the winter lows as well as the summer highs of the scenario, in combination with the species' critical upper and lower thermal limits. We find conditions for high growth and consumption rates generally lead to high bioaccumulation. However, this can be confounded by predator-prey dynamics, as mismatches in the temperature preferences of predator and prey can lead to mismatches in relative growth and uptake rates. As predator-prey dynamics are expected to undergo substantial shifts with changing climate, these relative thermal sensitivities will be key in determining the implications of climate change for bioaccumulation, particularly in top predator species.

Predicted climate change in the Andes will require plant species to migrate upslope to avoid extinction. Central to predictions of species responses to climate change is an understanding of species distributions along environmental gradients. Environmental gradients are frequently modelled as abiotic, but biotic interactions can play important roles in setting species distributions, abundances, and life history traits. Biotic interactions also have the potential to influence species responses to climate change, yet they remain mostly unquantified. An important interaction long studied in tropical forests is postdispersal seed predation which has been shown to affect the population dynamics, community structure, and diversity of plant species in time and space. This paper presents a comparative seed predation study of 24 species of tropical trees across a 2.5 km elevation gradient in the Peruvian Andes and quantifies seed predation variation across the elevational gradient. We then use demographic modelling to assess effects of the observed variation in seed predation on population growth rates in response to observed increasing temperatures in the area. We found marked variation among species in total seed predation depending on the major seed predator of the species and consistent changes in seed predation across the gradient. There was a significant increase in seed survival with increasing elevation, a trend that appears to be driven by regulation of seed predators via top-down forces in the lowlands giving way to bottom-up (productivity) regulation at mid- to high elevations, resulting in a ninefold increase in effective fecundity for trees at high elevations. This potential increase in seed crop size strongly affects modelled plant population growth and seed dispersal distances, increasing population migration potential in the face of climate change. These results also indicate that species interactions can have effects on par with climate in species responses to global change.

In this paper, we present a new approach, based on a mixed model procedure, to quantify the tree-ring-based growth-climate relationship of trembling aspen along a latitudinal gradient from 46 to 54 °N in eastern Canada. This approach allows breaking down the growth response into general intersite and local climatic responses, and analyzing variations of absolute ring width as well as interannual variations in tree growth. The final model also integrates nonclimatic variables such as soil characteristics and the occurrence of insect outbreaks into the growth predictions. Tree level random effects on growth were important as intercepts but were nonsignificant for the climatic variables, indicating that a single climate-growth relationship was justified in our case. The response of tree growth to climate showed, however, a strong dependence on the spatial scale at which the analysis was performed. Intersite variations in tree growth were mostly dependent on variations in the thermal heat sum, a variable that showed low interannual and high intersite variation. When variation for a single site was analyzed, other variables showed up to be important while the heat sum was unimportant. Finally, future growth under six different climate change scenarios was simulated in order to study the potential impact of climate change. Results suggest only moderate growth increases in the northern portion of the gradient and a growth decrease in the southern portion under future climatic conditions.

Lichens are thought to be sensitive indicators of global warming, as the spread of several thermophilous epiphytes in north-western Central Europe has been attributed to late 20th century warming. In the present paper, the potential contribution of late 20th century warming to the decline of arctic-alpine and boreal-montane lichen species is analyzed. Relevant ecological groups of lichens include terricolous heathland species, saxicolous species of exposed rock outcrops and boulder fields as well as epiphytes of mountain forests. These three groups of lichens experienced significant declines before the onset of late 20th century warming in the 1970s. These declines can be attributed to the abandonment of traditional land use systems in the case of the heathland lichens, increased recreational use of the exposed summits usually inhabited by cold-tolerant saxicolous lichens, and to high atmospheric SO 2 levels in the mid-20th century, but are probably not directly connected to global warming.

The North China Plain (NCP) is the most important agricultural production area in China. Crop production in the NCP is sensitive to changes in both climate and management practices. While previous studies showed a negative impact of climatic change on crop yield since 1980s, the confounding effects of climatic and agronomic factors have not been separately investigated. This paper used 25 years of crop data from three locations (Nanyang, Zhengzhou and Luancheng) across the NCP, together with daily weather data and crop modeling, to analyse the contribution of changes in climatic and agronomic factors to changes in grain yields of wheat and maize. The results showed that the changes in climate were not uniform across the NCP and during different crop growth stages. Warming mainly occurred during the vegetative (preflowering) growth stage of wheat and maize, while there was a cooling trend or no significant change in temperatures during the postflowering stage of wheat (spring) or maize (autumn). If varietal effects were excluded, warming during vegetative stages would lead to a reduction in the length of the growing period for both crops, generally leading to a negative impact on crop production. However, autonomous adoption of new crop varieties in the NCP was able to compensate the negative impact of climatic change. For both wheat and maize, the varietal changes helped stabilize the length of preflowering period against the shortening effect of warming and, together with the slightly reduced temperature in the postflowering period, extend the length of the grain-filling period. The combined effect led to increased wheat yield at Zhengzhou and Luancheng; increased maize yield at Nanyang and Luancheng; stabilized wheat yield at Nanyang, and a slight reduction in maize yield at Zhengzhou, compared with the yield change caused entirely by climatic change.

Global climate change is the major and most urgent global environmental issue. Australia is already experiencing climate change as evidenced by higher temperatures and more frequent and severe droughts. These impacts are compounded by increasing land use pressures on natural resources and native ecosystems. This paper provides a synthesis of the interactions, feedbacks and risks of natural climate variability, climate change and land use/land cover change (LUCC) impacting on the Australian continent and how they vary regionally. We review evidence of climate change and underlying processes resulting from interactions between global warming caused by increased concentration of atmospheric greenhouse gases and modification of the land surface. The consequences of ignoring the effect of LUCC on current and future droughts in Australia could have catastrophic consequences for the nation's environment, economy and communities. We highlight the need for more integrated, long-term and adaptive policies and regional natural resource management strategies that restore the beneficial feedbacks between native vegetation cover and local-regional climate, to help ameliorate the impact of global warming.

Some expected changes in climate resulting from human greenhouse gas emissions are clear and well documented, but others may be harder to predict because they involve extreme weather events or heretofore unusual combinations of weather patterns. One recent example of unusual weather that may become more frequent with climate change occurred in early spring 2007 when a large Arctic air mass moved into the eastern United States following a very warm late winter. In this paper, we document effects of this freeze event on Walker Branch, a well-studied stream ecosystem in eastern Tennessee. The 2007 spring freeze killed newly grown leaf tissues in the forest canopy, dramatically increasing the amount of light reaching the stream. Light levels at the stream surface were sustained at levels considerably above those normal for the late spring and summer months due to the incomplete recovery of canopy leaf area. Increased light levels caused a cascade of ecological effects in the stream beginning with considerably higher (two– three times) rates of gross primary production (GPP) during the late spring and summer months when normally low light levels severely limit stream GPP. Higher rates of stream GPP in turn resulted in higher rates of nitrate (NO3 ) uptake by the autotrophic community and lower NO3 concentrations in stream water. Higher rates of stream GPP in summer also resulted in higher growth rates of a dominant herbivore, the snail Elimia clavaeformis. Typically, during summer months net NO3 uptake and snail growth rates are zero to negative; however, in 2007 uptake and growth were maintained at moderate levels. These results show how changes in forest vegetation phenology can have dramatic effects on stream productivity at multiple trophic levels and on nutrient cycling as a result of tight coupling of forest and stream ecosystems. Thus, climate change-induced changes in canopy structure and phenology may lead to large effects on stream ecosystems in the future.

The lowland peatlands of south-east Asia represent an immense reservoir of fossil carbon and are reportedly responsible for 30% of the global carbon dioxide (CO2) emissions from Land Use, Land Use Change and Forestry. This paper provides a review and meta-analysis of available literature on greenhouse gas fluxes from tropical peat soils in south-east Asia. As in other parts of the world, water level is the main control on greenhouse gas fluxes from south-east Asian peat soils. Based on subsidence data we calculate emissions of at least 900 g CO2 m−2 a−1 (∼250 g C m−2 a−1) for each 10 cm of additional drainage depth. This is a conservative estimate as the role of oxidation in subsidence and the increased bulk density of the uppermost drained peat layers are yet insufficiently quantified. The majority of published CO2 flux measurements from south-east Asian peat soils concerns undifferentiated respiration at floor level, providing inadequate insight on the peat carbon balance. In contrast to previous assumptions, regular peat oxidation after drainage might contribute more to the regional long-term annual CO2 emissions than peat fires. Methane fluxes are negligible at low water levels and amount to up to 3 mg CH4 m−2 h−1 at high water levels, which is low compared with emissions from boreal and temperate peatlands. The latter emissions may be exceeded by fluxes from rice paddies on tropical peat soil, however. N2O fluxes are erratic with extremely high values upon application of fertilizer to wet peat soils. Current data on CO2 and CH4 fluxes indicate that peatland rewetting in south-east Asia will lead to substantial reductions of net greenhouse gas emissions. There is, however, an urgent need for further quantitative research on carbon exchange to support the development of consistent policies for climate change mitigation.

Global climate change is leading to redistribution of marine species and altering ecosystem dynamics. Given recent poleward range extension of the barrens-forming sea urchin Centrostephanus rodgersii (Diadematidae) from mainland Australia to Tasmania, there is a need to understand the population dynamics of this ecologically important species in the Tasmanian environment. This paper informs possible population dynamics of C. rodgersii in Tasmania by examining its reproductive ecology in this new environment. Reproductive periodicity (gonad index and propensity to spawn) was assessed bimonthly over 18 months at four sites in eastern Tasmania spanning ~­2° in latitude. At all sites, C. rodgersii displayed a strong seasonal cycle in gonad production with major spawning occurring in winter (~August) at minimum annual water temperature. Gametes from Tasmanian C. rodgersii were viable as determined by fertilization and early development trials. However, development to the two-arm stage at ~­3 weeks was strongly dependent on water temperature across the 8-20 °C temperature range, with poor development occurring below 12 °C. The range of temperatures tolerated by Tasmanian C. rodgersii larvae was similar to that of larvae from its native New South Wales range, indicating that this species has not undergone an adaptive shift to the cooler Tasmanian environment. There was also no evidence for an adaptive shift in reproductive phenology. Importantly, coastal water temperatures in eastern Tasmania during the peak spawning in August fluctuate about the 12 °C larval development threshold. Recent warming of the eastern Tasmanian coast and further warming predicted by global climate change will result in an environment increasingly favourable for the reproduction and development of C. rodgersii .

The expectation that atmospheric warming will be most pronounced at higher latitudes means that Arctic and montane systems, with predominantly organic soils, will be particularly influenced by climate change. One group of soil fauna, the enchytraeids, is commonly the major soil faunal component in specific biomes, frequently exceeding above-ground fauna in biomass terms. These organisms have a crucial role in carbon turnover in organic rich soils and seem particularly sensitive to temperature changes. In order to predict the impacts of climate change on this important group of soil organisms we reviewed data from 44 published papers using a combination of conventional statistical techniques and meta-analysis. We focused on the effects of abiotic factors on total numbers of enchytraeids (a total of 611 observations) and, more specifically, concentrated on total numbers, vertical distribution and age groupings of the well-studied species Cognettia sphagnetorum (228 observations). The results highlight the importance of climatic factors, together with vegetation and soil type in determining global enchytraeid distribution; in particular, cold and wet environments with mild summers are consistently linked to greater densities of enchytraeids. Based on the upper temperature distribution limits reported in the literature, and identified from our meta-analyses, we also examined the probable future geographical limits of enchytraeid distribution in response to predicted global temperature changes using the HadCM3 model climate output for the period between 2010 and 2100. Based on the existing data we identify that a maximum mean annual temperature threshold of 16 °C could be a critical limit for present distribution of field populations, above which their presence would decline markedly, with certain key species, such as C. sphagnetorum, being totally lost from specific regions. We discuss the potential implications for carbon turnover in these organic soils where these organisms currently dominate and, consequently, their future role as C sink/source in response to climate change.

Bioclimatic models are the primary tools for simulating the impact of climate change on species distributions. Part of the uncertainty in the output of these models results from uncertainty in projections of future climates. To account for this, studies often simulate species responses to climates predicted by more than one climate model and/or emission scenario. One area of uncertainty, however, has remained unexplored: internal climate model variability. By running a single climate model multiple times, but each time perturbing the initial state of the model slightly, different but equally valid realizations of climate will be produced. In this paper, we identify how ongoing improvements in climate models can be used to provide guidance for impacts studies. In doing so we provide the first assessment of the extent to which this internal climate model variability generates uncertainty in projections of future species distributions, compared with variability between climate models. We obtained data on 13 realizations from three climate models (three from CSIRO Mark2 v3.0, four from GISS AOM, and six from MIROC v3.2) for two time periods: current (1985–1995) and future (2025–2035). Initially, we compared the simulated values for each climate variable (P, Tmax, Tmin, and Tmean) for the current period to observed climate data. This showed that climates simulated by realizations from the same climate model were more similar to each other than to realizations from other models. However, when projected into the future, these realizations followed different trajectories and the values of climate variables differed considerably within and among climate models. These had pronounced effects on the projected distributions of nine Australian butterfly species when modelled using the BIOCLIM component of DIVA-GIS. Our results show that internal climate model variability can lead to substantial differences in the extent to which the future distributions of species are projected to change. These can be greater than differences resulting from between-climate model variability. Further, different conclusions regarding the vulnerability of species to climate change can be reached due to internal model variability. Clearly, several climate models, each represented by multiple realizations, are required if we are to adequately capture the range of uncertainty associated with projecting species distributions in the future.

Lowland boreal forest ecosystems in Alaska are dominated by wetlands comprised of a complex mosaic of fens, collapse-scar bogs, low shrub/scrub, and forests growing on elevated ice-rich permafrost soils. Thermokarst has affected the lowlands of the Tanana Flats in central Alaska for centuries, as thawing permafrost collapses forests that transition to wetlands. Located within the discontinuous permafrost zone, this region has significantly warmed over the past half-century, and much of these carbon-rich permafrost soils are now within ~0.5 °C of thawing. Increased permafrost thaw in lowland boreal forests in response to warming may have consequences for the climate system. This study evaluates the trajectories and potential drivers of 60 years of forest change in a landscape subjected to permafrost thaw in unburned dominant forest types (paper birch and black spruce) associated with location on elevated permafrost plateau and across multiple time periods (1949, 1978, 1986, 1998, and 2009) using historical and contemporary aerial and satellite images for change detection. We developed (i) a deterministic statistical model to evaluate the potential climatic controls on forest change using gradient boosting and regression tree analysis, and (ii) a 30 × 30 m land cover map of the Tanana Flats to estimate the potential landscape-level losses of forest area due to thermokarst from 1949 to 2009. Over the 60-year period, we observed a nonlinear loss of birch forests and a relatively continuous gain of spruce forest associated with thermokarst and forest succession, while gradient boosting/regression tree models identify precipitation and forest fragmentation as the primary factors controlling birch and spruce forest change, respectively. Between 1950 and 2009, landscape-level analysis estimates a transition of ~15 km² or ~7% of birch forests to wetlands, where the greatest change followed warm periods. This work highlights that the vulnerability and resilience of lowland ice-rich permafrost ecosystems to climate changes depend on forest type.

The recent quantification of changes in time series of phenology data with Bayesian methods has provided compelling evidence for changes during the last 20 years. In this paper we correlate the phenological observations with spring temperature time series. We provide quantitative answers to the question whether changes in temperature and phenological time series should be regarded as coherent or independent. For the three considered species snowdrops, cherry and lime tree we find factors of 1.05, 2.19 and 3.26, respectively, in favor of coherence. The functional behavior and the trend in the temperature time series are presented. They amount to 0.151Cyr � 1 for the January‐ March average, 0.091Cyr � 1 for February‐April and 0.11Cyr � 1 for March‐May in 2002. In addition, we compare blossom trends for the coherent and independent hypotheses and find that the transition from trend values slightly positive before 1970 to strongly negative at present becomes sharper as the temperature data are included in the analysis.

Energy crops currently contribute a relatively small proportion to the total energy produced from biomass each year, but the proportion is set to grow over the next few decades. This paper reviews the current status of energy crops and their conversion technologies, assesses their potential to contribute to global energy demand and climate mitigation over the next few decades, and examines the future prospects. Previous estimates have suggested a technical potential for energy crops of?400?EJ?yr?1 by 2050. In a new analysis based on energy crop areas for each of the IPCC SRES scenarios in 2025 (as projected by the IMAGE 2.2 integrated assessment model), more conservative dry matter and energy yield estimates and an assessment of the impact on non-CO2 greenhouse gases were used to estimate the realistically achievable potential for energy crops by 2025 to be between 2 and 22?EJ?yr?1, which will offset?100-2070?Mt?CO2-eq.?yr?1. These results suggest that additional production of energy crops alone is not sufficient to reduce emissions to meet a 550??mol?mol?1 atmospheric CO2 stabilization trajectory, but is sufficient to form an important component in a portfolio of climate mitigation measures, as well as to provide a significant sustainable energy resource to displace fossil fuel resources. Realizing the potential of energy crops will necessitate optimizing the dry matter and energy yield of these crops per area of land through the latest biotechnological routes, with or without the need for genetic modification. In future, the co-benefits of bioenergy production will need to be optimized and methods will need to be developed to extract and refine high-value products from the feedstock before it is used for energy production.

Department of Geography, University of Wisconsin-Madison, 550 North ParkStreet, Madison, WI 53706, USAThe influence of climate on forest change during thepast century in the eastern United States was evalu-ated in a recent paper (Nowacki & Abrams, 2014)that centers on an increase in ‘highly competitivemesophytic hardwoods’ (Nowacki & Abrams, 2008)and a concomitant decrease in the more xerophyticQuercus species. Nowacki & Abrams (2014) con-cluded that climate change has not contributed sig-nificantly to observed changes in forest composition.However, the authors restrict their focus to a singleelement of climate: increasing temperature since theend of the Little Ice Age ca. 150 years ago. In theirstudy, species were binned into four classifications(e.g., Acer saccharum – ‘cool-adapted’, Acer rubrum –‘warm-adapted’) based on average annual tempera-ture within each species range in the United States,reducing the multifaceted character of climate into asingle, categorical measure. The broad temperatureclasses not only veil the many biologically relevantaspects of temperature (e.g., seasonal and extremetemperatures) but they may also mask other influ-ences, both climatic (e.g., moisture sensitivity) andnonclimatic (e.g., competition).Understanding the primary drivers of forest changeis critically important. However, using annual tem-perature reduces the broad spectrum of climaticinfluence on forests (e.g., Jackson & Overpeck, 2000;Jackson et al., 2009) to a single variable. Tsuga canad-ensis illustrates one example of the complex interac-tion between trees and temperature. In the southernpart of its range, Tsuga canadensis growth is weakly,but positively correlated with early growing-seasontemperature. However, this relationship becomesstronger and shifts to later in the season toward thenorthern part of its range (Cook & Cole, 1991). More-over, Tsuga canadensis growth is significantly andnegatively correlated with just May temperaturesduring the current growing season in the northeast-ern United States (Cook, 1991; Cook & Cole, 1991;Vaganov et al., 2011), while in the southeastern Uni-ted States it is strongly and negatively correlatedwith summer (June–August) temperatures (Hart et al.,2010). Trees can also be sensitive to diverse and ofteninteracting climate variables at various stages of theirlife cycles (Jackson et al., 2009). Interactions betweenprecipitation and temperature are clearly important(Harsch & Hille Ris Lambers, 2014; Martin-Benito &Pederson, accepted), and often lead to counterintui-tive responses. For example, some plant species thatwould have been expected to move north and ups

The Kyoto protocol requires countries to provide national inventories for a list of greenhouse gases including N2O. A standard methodology proposed by the Intergovernmental Panel on Climate Change (IPCC) estimates direct N2O emissions from soils as a constant fraction (1.25%) of the nitrogen input. This approach is insensitive to environmental variability. A more dynamic approach is needed to establish reliable N2O emission inventories and to propose efficient mitigation strategies. The objective of this paper is to develop a model that allows the spatial and temporal variation in environmental conditions to be taken into account in national inventories of direct N2O emissions. Observed annual N2O emission rates are used to establish statistical relationships between N2O emissions, seasonal climate and nitrogen-fertilization rate. Two empirical models, MCROPS and MGRASS, were developed for croplands and grasslands. Validated with an independent data set, MCROPS shows that spring temperature and summer precipitation explain 35% of the variance in annual N2O emissions from croplands. In MGRASS, nitrogen-fertilization rate and winter temperature explain 48% of the variance in annual N2O emissions from grasslands. Using long-term climate observations (1900-2000), the sensitivity of the models with climate variability is estimated by comparing the year-to-year prediction of the model to the precision obtained during the validation process. MCROPS is able to capture interannual variability of N2O emissions from croplands. However, grassland emissions show very small interannual variations, which are too small to be detectable by MGRASS. MCROPS and MGRASS improve the statistical reliability of direct N2O emissions compared with the IPCC default methodology. Furthermore, the models can be used to estimate the effects of interannual variation in climate, climate change on direct N2O emissions from soils at the regional scale.

A strong relationship between dissolved organic carbon (DOC) and sulphate (SO42−) dynamics under drought conditions has been revealed from analysis of a 10-year time series (1993–2002). Soil solution from a blanket peat at 10 cm depth and stream water were collected at biweekly and weekly intervals, respectively, by the Environmental Change Network at Moor House-Upper Teesdale National Nature Reserve in the North Pennine uplands of Britain. DOC concentrations in soil solution and stream water were closely coupled, displaying a strong seasonal cycle with lowest concentrations in early spring and highest in late summer/early autumn. Soil solution DOC correlated strongly with seasonal variations in soil temperature at the same depth 4-weeks prior to sampling. Deviation from this relationship was seen, however, in years with significant water table drawdown (>−25 cm), such that DOC concentrations were up to 60% lower than expected. Periods of drought also resulted in the release of SO42−, because of the oxidation of inorganic/organic sulphur stored in the peat, which was accompanied by a decrease in pH and increase in ionic strength. As both pH and ionic strength are known to control the solubility of DOC, inclusion of a function to account for DOC suppression because of drought-induced acidification accounted for more of the variability of DOC in soil solution (R2=0.81) than temperature alone (R2=0.58). This statistical model of peat soil solution DOC at 10 cm depth was extended to reproduce 74% of the variation in stream DOC over this period. Analysis of annual budgets showed that the soil was the main source of SO42− during droughts, while atmospheric deposition was the main source in other years. Mass balance calculations also showed that most of the DOC originated from the peat. The DOC flux was also lower in the drought years of 1994 and 1995, reflecting low DOC concentrations in soil and stream water. The analysis presented in this paper suggests that lower concentrations of DOC in both soil and stream waters during drought years can be explained in terms of drought-induced acidification. As future climate change scenarios suggest an increase in the magnitude and frequency of drought events, these results imply potential for a related increase in DOC suppression by episodic acidification.

The identification of changes in observational data relating to the climate change hypothesis remains a topic of paramount importance. In particular, scientifically sound and rigorous methods for detecting changes are urgently needed. In this paper, we develop a Bayesian approach to nonparametric function estimation. The method is applied to blossom time series of Prunus avium L., Galanthus nivalis L. and Tilia platyphyllos SCOP. The functional behavior of these series is represented by three different models: the constant model, the linear model and the one change point model. The one change point model turns out to be the preferred one in all three data sets with considerable discrimination of the other alternatives. In addition to the functional behavior, rates of change in terms of days per year were also calculated. We obtain also uncertainty margins for both function estimates and rates of change. Our results provide a quantitative representation of what was previously inferred from the same data by less involved methods.

Experimental evidence regarding the responses of cereal aphids to rising atmospheric CO2 has been ambiguous. Some studies suggest increased population sizes under future CO2 levels, others suggest decreased population sizes, and still others suggest little or no difference. Recently, Newman et al. (2003) constructed a general mathematical model of the aphid–grass interaction to investigate whether or not we should, in fact, expect a general aphid response to rising CO2. They concluded that aphid populations are likely to be larger under future CO2 concentrations if soil N levels are high, the aphid species' nitrogen requirement is low and the aphid species' density-dependent response in winged morph production is weak. In that model, and in field experiments, CO2 concentration influences aphid population dynamics through the effect it has on plant quality. However, future CO2 concentrations are also likely to be accompanied by higher ambient temperatures, a combination that has received little focus to date. In the present paper, the Newman et al. model is used to consider the combined effects of increased CO2 concentrations and temperature on aphid population sizes. It is concluded that, when both factors are elevated, aphid population dynamics will be more similar to current ambient conditions than expected from the results of experiments studying either factor alone. This result has important implications for future experimentation.

This paper, based on a literature review, presents a quantitative overview of the role of natural disturbances in European forests from 1850 to 2000. Such an overview provides a basis for modelling the possible impacts of climate change and enables one to assess trends in disturbance regimes in different countries and/or periods. Over the period 1950–2000, an annual average of 35 million m3 wood was damaged by disturbances; there was much variation between years. Storms were responsible for 53% of the total damage, fire for 16%, snow for 3% and other abiotic causes for 5%. Biotic factors caused 16% of the damage, and half of this was caused by bark beetles. For 7% of the damage, no cause was given or there was a combination of causes. The 35 million m3 of damage is about 8.1% of the total fellings in Europe and about 0.15% of the total volume of growing stock. Over the period 1961–2000, the average annual area of forest fires was 213 000 ha, which is 0.15% of the total forest area in Europe. Most types of damage seem to be increasing. This is partly an artefact of the improved availability of information. The most likely explanations for an increase in damage from disturbances are changes in forest management and resulting changes in the condition of the forest. Forest area, average volume of growing stock and average stand age have increased considerably, making the forest more vulnerable and increasing the resources that can be damaged. Since forest resources are expected to continue to increase, it is likely that damage from disturbances will also increase in future.

The need for anticipating and mitigating the potential effects of climate change on biodiversity has triggered the development of predictive tools to provide quantitative scenarios to guide decision making (Pereira et al., 2010). Notably, the recently established ‘Intergovernmental Platform on Biodiversity and Ecosystem Services’ (IPBES) will rely on these predictive tools. Between 1990 and 2000, statistical models that relate species occurrences to climatic variables were developed to predict species ranges and to forecast potential changes under the strong assumption that the detected relationships between the species of interest and the selected climatic variables will hold into the future (reviewed in Guisan & Thuiller, 2005). Since then, a variety of statistical approaches have been proposed and compared (see Thuiller, same issue). In the early 2000s, with the rise of statistical software such as Splus, SAS or later R, several algorithms became available to ecologists to propose species range change scenarios based on the IPCC climate models and SRES scenarios (Nakicenovic & Swart, 2000). Generalised linear models, generalised additive models, regression trees, genetic algorithms or artificial neural networks were used increasingly to assess the potential impacts of climate change on biodiversity. During this period I stumbled upon the issue that although different algorithms are likely to give the same answer under current (calibration) conditions, they tended to drastically diverge when they were used to predict species ranges under future climate. This was published with Global Change Biology under this paper “Patterns and uncertainties of species’ range shifts under climate change” (Thuiller, 2004). Although ten years later I find this result relatively obvious, at the time I was amazed that seemingly subtle differences between algorithms could actually lead to sharp divergences when projecting into the future. A species could indeed be predicted committed to extinction with one algorithm, and under range expansion with another. Since then, substantial progress has been made toward understanding why such strong discrepancies could occur (e.g. collinearity, complex interactions between variables or incomplete climatic niche estimations) and several analyses have confirmed this result (Lawler et al., 2006, Pearson et al., 2006). How to deal with variability from different initial conditions, algorithms, parameterisation and bounding conditions is still an open question in ecology and other fields of science (Araujo & New, 2007). As reviewed in Araujo and New (2007), an ensemble of forecasts is one of the most accepted ways to account for projection variability since it relies on multiple projections across sets of initial conditions, algorithms (e.g. generalised linear models or boosted regression trees), parameters (e.g. quadratic vs polynomial terms, number of regression trees in a random forest) and bounding conditions (e.g. different climate models). Although ensemble forecasting was a relatively well-accepted approach in other fields such as economics or climatology, it was relatively unknown in ecology in the early 2000s and did not emerge as a plausible alternative to single initial data-algorithms until 2004 (Thuiller, 2004) and 2007 (Araujo & New, 2007). The major advantage of combining a set of forecasts is to give a probability distribution per pixel as opposed to a single crude value. This allows for extraction of average predictions as well as confidence intervals given varying input data, algorithms, parameterisation and bounding conditions. Still, although such an approach is now a common practice (Marmion et al., 2009), ensemble forecasts are often used as a single forecast by extracting an average or a weighted average based on different evaluation techniques, without considering the variability behind those averages and without considering which metric to use for scoring the different projections. If forecasts have to be used in conservation planning or to be used guiding tools for decision-making, they should present not only the main trend but also the variability around this trend.

International audience; Antarctic and Southern Ocean (ASO) marine ecosystems have been changing for at least the last 30 years, including in response to increasing ocean temperatures and changes in the extent and seasonality of sea-ice; the magnitude and direction of these changes differ between regions around Antarctica that could see populations of the same species changing differently in different regions. This paper reviews current and expected changes in ASO physical habitats in response to climate change. It then reviews how these changes may impact the autecology of marine biota of this polar region: microbes, zooplankton, salps, Antarctic krill, fish, cephalopods, marine mammals, seabirds, and benthos. The general prognosis for ASO marine habitats is for an overall warming and freshening, strengthening of westerly winds, with a potential pole-ward movement of those winds and the frontal systems, and an increase in ocean eddy activity. Many habitat parameters will have regionally specific changes, particularly relating to sea-ice characteristics and seasonal dynamics. Lower trophic levels are expected to move south as the ocean conditions in which they are currently found move pole-ward. For Antarctic krill and finfish, the latitudinal breadth of their range will depend on their tolerance of warming oceans and changes to productivity. Ocean acidification is a concern not only for calcifying organisms, but also for crustaceans such as Antarctic krill; it is also likely to be the most important change in benthic habitats over the coming century. For marine mammals and birds, the expected changes primarily relate to their flexibility in moving to alternative locations for food and the energetic cost of longer or more complex foraging trips for those that are bound to breeding colonies. Few species are sufficiently well studied to make comprehensive species-specific vulnerability assessments possible. Priorities for future work are discussed. This article is protected by copyright. All rights reserved.