Impacts of climate and land use on N2O and CH4 fluxes from tropical ecosystems in the Mt. Kilimanjaro region,Tanzania

In this study, we quantify the impacts of climate and land use on soil N₂O and CH₄ fluxes from tropical forest, agroforest, arable and savanna ecosystems in Africa. To do so, we measured greenhouse gases (GHG) fluxes from 12 different ecosystems along climate and land‐use gradients at Mt. Kilimanjaro, combining long‐term in situ chamber and laboratory soil core incubation techniques. Both methods showed similar patterns of GHG exchange. Although there were distinct differences from ecosystem to ecosystem, soils generally functioned as net sources and sinks for N₂O and CH₄ respectively. N₂O emissions correlated positively with soil moisture and total soil nitrogen content. CH₄ uptake rates correlated negatively with soil moisture and clay content and positively with SOC. Due to moderate soil moisture contents and the dominance of nitrification in soil N turnover, N₂O emissions of tropical montane forests were generally low (<1.2 kg N ha^?1 year^?1), and it is likely that ecosystem N losses are driven instead by nitrate leaching (~10 kg N ha^?1 year^?1). Forest soils with well‐aerated litter layers were a significant sink for atmospheric CH₄ (up to 4 kg C ha^?1 year^?1) regardless of low mean annual temperatures at higher elevations. Land‐use intensification significantly increased the soil N₂O source strength and significantly decreased the soil CH₄ sink. Compared to decreases in aboveground and belowground carbon stocks enhanced soil non‐CO₂ GHG emissions following land‐use conversion from tropical forests to homegardens and coffee plantations were only a small factor in the total GHG budget. However, due to lower ecosystem carbon stock changes, enhanced N₂O emissions significantly contributed to total GHG emissions following conversion of savanna into grassland and particularly maize. Overall, we found that the protection and sustainable management of aboveground and belowground carbon and nitrogen stocks of agroforestry and arable systems is most crucial for mitigating GHG emissions from land‐use change.     

Impacts of tropospheric ozone and climate change on net primary productivity and net carbon exchange of China's forest ecosystems

Aim We investigated how ozone pollution and climate change/variability have interactively affected net primary productivity (NPP) and net carbon exchange (NCE) across China's forest ecosystem in the past half century. Location Continental China. Methods Using the dynamic land ecosystem model (DLEM) in conjunction with 10‐km‐resolution gridded historical data sets (tropospheric O₃ concentrations, climate variability/change, and other environmental factors such as land‐cover/land‐use change (LCLUC), increasing CO₂ and nitrogen deposition), we conducted nine simulation experiments to: (1) investigate the temporo‐spatial patterns of NPP and NCE in China's forest ecosystems from 1961–2005; and (2) quantify the effects of tropospheric O₃ pollution alone or in combination with climate variability and other environmental stresses on forests' NPP and NCE. Results China's forests acted as a carbon sink during 1961–2005 as a result of the combined effects of O₃, climate, CO₂, nitrogen deposition and LCLUC. However, simulated results indicated that elevated O₃ caused a 7.7% decrease in national carbon storage, with O₃‐induced reductions in NCE (Pg C year^?1) ranging from 0.4–43.1% among different forest types. Sensitivity experiments showed that climate change was the dominant factor in controlling changes in temporo‐spatial patterns of annual NPP. The combined negative effects of O₃ pollution and climate change on NPP and NCE could be largely offset by the positive fertilization effects of nitrogen deposition and CO₂. Main conclusions In the future, tropospheric O₃ should be taken into account in order to fully understand the variations of carbon sequestration capacity of forests and assess the vulnerability of forest ecosystems to climate change and air pollution. Reducing air pollution in China is likely to increase the resilience of forests to climate change. This paper offers the first estimate of how prevention of air pollution can help to increase forest productivity and carbon sequestration in China's forested ecosystems.     

Accelerated terrestrial ecosystem carbon turnover and its drivers

The terrestrial carbon cycle has been strongly influenced by human‐induced CO₂ increase, climate change, and land use change since the industrial revolution. These changes alter the carbon balance of ecosystems through changes in vegetation productivity and ecosystem carbon turnover time (τ_eco). Even though numerous studies have drawn an increasingly clear picture of global vegetation productivity changes, global changes in τ_eco are still unknown. In this study, we analyzed the changes of τ_eco between the 1860s and the 2000s and their drivers, based on theory of dynamic carbon cycle in non‐steady state and process‐based ecosystem model. Results indicate that τ_eco has been reduced (i.e., carbon turnover has accelerated) by 13.5% from the 1860s (74 years) to the 2000s (64 years), with reductions of 1 year of carbon residence times in vegetation (r_veg) and of 9 years in soil (r_soil). Additionally, the acceleration of τ_eco was examined at biome scale and grid scale. Among different driving processes, land use change and climate change were found to be the major drivers of turnover acceleration. These findings imply that carbon fixed by plant photosynthesis is being lost from ecosystems to the atmosphere more quickly over time, with important implications for the climate‐carbon cycle feedbacks.     

Land management and climate change determine second‐generation bioenergy potential of the US Northern Great Plains

Bioenergy with carbon capture and storage (BECCS) has been proposed as a potential climate mitigation strategy raising concerns over trade‐offs with existing ecosystem services. We evaluate the feasibility of BECCS in the Upper Missouri River Basin (UMRB), a landscape with diverse land use, ownership, and bioenergy potential. We develop land‐use change scenarios and a switchgrass (Panicum virgatum L.) crop functional type to use in a land‐surface model to simulate second‐generation bioenergy production. By the end of this century, average annual switchgrass production over the UMRB ranges from 60 to 210 Tg dry mass/year and is dependent on the Representative Concentration Pathway for greenhouse gas emissions and on land‐use change assumptions. Under our simple phase‐in assumptions this results in a cumulative total production of 2,000–6,000 Tg C over the study period with the upper estimates only possible in the absence of climate change. Switchgrass yields decreased as average CO₂ concentrations and temperatures increased, suggesting the effect of elevated atmospheric CO₂ was small because of its C4 photosynthetic pathway. By the end of the 21st century, the potential energy stored annually in harvested switchgrass averaged between 1 and 4 EJ/year assuming perfect conversion efficiency, or an annual electrical generation capacity of 7,000–28,000 MW assuming current bioenergy efficiency rates. Trade‐offs between bioenergy and ecosystem services were identified, including cumulative direct losses of 1,000–2,600 Tg C stored in natural ecosystems from land‐use change by 2090. Total cumulative losses of ecosystem carbon stocks were higher than the potential ~300 Tg C in fossil fuel emissions from the single largest power plant in the region over the same time period, and equivalent to potential carbon removal from the atmosphere from using biofuels grown in the same region. Numerous trade‐offs from BECCS expansion in the UMRB must be balanced against the potential benefits of a carbon‐negative energy system.     

Critical land change information enhances the understanding of carbon balance in the United States

Large‐scale terrestrial carbon (C) estimating studies using methods such as atmospheric inversion, biogeochemical modeling, and field inventories have produced different results. The goal of this study was to integrate fine‐scale processes including land use and land cover change into a large‐scale ecosystem framework. We analyzed the terrestrial C budget of the conterminous United States from 1971 to 2015 at 1‐km resolution using an enhanced dynamic global vegetation model and comprehensive land cover change data. Effects of atmospheric CO₂ fertilization, nitrogen deposition, climate, wildland fire, harvest, and land use/land cover change (LUCC) were considered. We estimate annual C losses from cropland harvest, forest clearcut and thinning, fire, and LUCC were 436.8, 117.9, 10.5, and 10.4 TgC/year, respectively. C stored in ecosystems increased from 119,494 to 127,157 TgC between 1971 and 2015, indicating a mean annual net C sink of 170.3 TgC/year. Although ecosystem net primary production increased by approximately 12.3 TgC/year, most of it was offset by increased C loss from harvest and natural disturbance and increased ecosystem respiration related to forest aging. As a result, the strength of the overall ecosystem C sink did not increase over time. Our modeled results indicate the conterminous US C sink was about 30% smaller than previous modeling studies, but converged more closely with inventory data.     

Changes in soil greenhouse gas fluxes by land use change from primary forest

Primary forest conversion is a worldwide serious problem associated with human disturbance and climate change. Land use change from primary forest to plantation, grassland or agricultural land may lead to profound alteration in the emission of soil greenhouse gases (GHG). Here, we conducted a global meta‐analysis concerning the effects of primary forest conversion on soil GHG emissions and explored the potential mechanisms from 101 studies. Our results showed that conversion of primary forest significantly decreased soil CO₂ efflux and increased soil CH₄ efflux, but had no effect on soil N₂O efflux. However, the effect of primary forest conversion on soil GHG emissions was not consistent across different types of land use change. For example, soil CO₂ efflux did not respond to the conversion from primary forest to grassland. Soil N₂O efflux showed a prominent increase within the initial stage after conversion of primary forest and then decreased over time while the responses of soil CO₂ and CH₄ effluxes were consistently negative or positive across different elapsed time intervals. Moreover, either within or across all types of primary forest conversion, the response of soil CO₂ efflux was mainly moderated by changes in soil microbial biomass carbon and root biomass while the responses of soil N₂O and CH₄ effluxes were related to the changes in soil nitrate and soil aeration‐related factors (soil water content and bulk density), respectively. Collectively, our findings highlight the significant effects of primary forest conversion on soil GHG emissions, enhance our knowledge on the potential mechanisms driving these effects and improve future models of soil GHG emissions after land use change from primary forest.     

A multi‐criteria based review of models that predict environmental impacts of land use‐change for perennial energy crops on water,carbon and nitrogen cycling

Reduction in energy sector greenhouse gas GHG emissions is a key aim of European Commission plans to expand cultivation of bioenergy crops. Since agriculture makes up 10–12% of anthropogenic GHG emissions, impacts of land‐use change must be considered, which requires detailed understanding of specific changes to agroecosystems. The greenhouse gas (GHG) balance of perennials may differ significantly from the previous ecosystem. Net change in GHG emissions with land‐use change for bioenergy may exceed avoided fossil fuel emissions, meaning that actual GHG mitigation benefits are variable. Carbon (C) and nitrogen (N) cycling are complex interlinked systems, and a change in land management may affect both differently at different sites, depending on other variables. Change in evapotranspiration with land‐use change may also have significant environmental or water resource impacts at some locations. This article derives a multi‐criteria based decision analysis approach to objectively identify the most appropriate assessment method of the environmental impacts of land‐use change for perennial energy crops. Based on a literature review and conceptual model in support of this approach, the potential impacts of land‐use change for perennial energy crops on GHG emissions and evapotranspiration were identified, as well as likely controlling variables. These findings were used to structure the decision problem and to outline model requirements. A process‐based model representing the complete agroecosystem was identified as the best predictive tool, where adequate data are available. Nineteen models were assessed according to suitability criteria, to identify current model capability, based on the conceptual model, and explicit representation of processes at appropriate resolution. FASSET, ECOSSE, ANIMO, DNDC, DayCent, Expert‐N, Ecosys, WNMM and CERES‐NOE were identified as appropriate models, with factors such as crop, location and data availability dictating the final decision for a given project. A database to inform such decisions is included.     

What does species richness tell us about functional trait diversity? Predictions and evidence for responses of species and functional trait diversity to land‐use change

In the conservation literature on land‐use change, it is often assumed that land‐use intensification drives species loss, driving a loss of functional trait diversity and ecosystem function. Modern research, however, does not support this cascade of loss for all natural systems. In this paper we explore the errors in this assumption and present a conceptual model taking a more mechanistic approach to the species–functional trait association in a context of land‐use change. We provide empirical support for our model's predictions demonstrating that the association of species and functional trait diversity follows various trajectories in response to land‐use change. The central premise of our model is that land‐use change impacts upon processes of community assembly, not species per se. From the model, it is clear that community context (i.e. type of disturbance, species pool size) will affect the response trajectory of the relationship between species and functional trait diversity in communities undergoing land‐use change. The maintenance of ecosystem function and of species diversity in the face of increasing land‐use change are complementary goals. The use of a more ecologically realistic model of responses of species and functional traits will improve our ability to make wise management decisions to achieve both aims in specific at‐risk systems.     

Biofuels agriculture: landscape‐scale trade‐offs between fuel,economics, carbon,energy, food,and fiber

First‐generation biofuels are an existing, scalable form of renewable energy of the type urgently required to mitigate climate change. In this study, we assessed the potential benefits, costs, and trade‐offs associated with biofuels agriculture to inform bioenergy policy. We assessed different climate change and carbon subsidy scenarios in an 11.9 million ha (5.48 million ha arable) region in southern Australia. We modeled the spatial distribution of agricultural production, full life‐cycle net greenhouse gas (GHG) emissions and net energy, and economic profitability for both food agriculture (wheat, legumes, sheep rotation) and biofuels agriculture (wheat, canola rotation for ethanol/biodiesel production). The costs, benefits, and trade‐offs associated with biofuels agriculture varied geographically, with climate change, and with the level of carbon subsidy. Below we describe the results in general and provide (in parentheses) illustrative results under historical mean climate and a carbon subsidy of A$20 t^?1 CO₂^?e. Biofuels agriculture was more profitable over an extensive area (2.85 million ha) of the most productive arable land and produced large quantities of biofuels (1.7 GL yr^?1). Biofuels agriculture substantially increased economic profit (145.8 million $A yr^?1 or 30%), but had only a modest net GHG abatement (?2.57 million t CO₂^?e yr^?1), and a negligible effect on net energy production (?0.11 PJ yr^?1). However, food production was considerably reduced in terms of grain (?3.04 million t yr^?1) and sheep meat (?1.89 million head yr^?1). Wool fiber production was also substantially reduced (?23.19 kt yr^?1). While biofuels agriculture can produce short‐term benefits, it also has costs, and the vulnerability of biofuels to climatic warming and drying renders it a myopic strategy. Nonetheless, in some areas the profitability of biofuels agriculture is robust to variation in climate and level of carbon subsidy and these areas may form part of a long‐term diversified mix of land‐use solutions to climate change if trade‐offs can be managed.     

Implications of emissions timing on the cost‐effectiveness of greenhouse gas mitigation strategies: application to forest bioenergy systems

Conventional cost‐effectiveness calculations ignore the implications of greenhouse gas (GHG) emissions timing and thus may not properly inform decision‐makers in the efficient allocation of resources to mitigate climate change. To begin to address this disconnect with climate change science, we modify the conventional cost‐effectiveness approach to account for emissions timing. GHG emissions flows occurring over time are translated into an ‘Equivalent Present Emission’ based on radiative forcing, enabling a comparison of system costs and emissions on a consistent present time basis. We apply this ‘Present Cost‐Effectiveness’ method to case studies of biomass‐based electricity generation (biomass co‐firing with coal, biomass cogeneration) to evaluate implications of forest carbon trade‐offs on the cost‐effectiveness of emission reductions. Bioenergy production from forest biomass can reduce forest carbon stocks, an immediate emissions source that contributes to atmospheric greenhouse gases. Forest carbon impacts thereby lessen emission reductions in the near‐term relative to the assumption of biomass ‘carbon neutrality’, resulting in higher costs of emission reductions when emissions timing is considered. In contrast, conventional cost‐effectiveness approaches implicitly evaluate strategies over an infinite analytical time horizon, underestimating nearer term emissions reduction costs and failing to identify pathways that can most efficiently contribute to climate change mitigation objectives over shorter time spans (e.g. up to 100 years). While providing only a simple representation of the climate change implications of emissions timing, the Present Cost‐Effectiveness method provides a straightforward approach to assessing the cost‐effectiveness of emission reductions associated with any climate change mitigation strategy where future GHG reductions require significant initial capital investment or increase near‐term emissions. Timing is a critical factor in determining the attractiveness of any investment; accounting for emissions timing can better inform decisions related to the merit of alternative resource uses to meet near‐, mid‐, and long‐term climate change mitigation objectives.     

Step back from the forest and step up to the Bonn Challenge: how a broad ecological perspective can promote successful landscape restoration

We currently face both an extinction and a biome crisis embedded in a changing climate. Many biodiverse ecosystems are being lost at far higher rates than they are being protected or ecologically restored. At the same time, natural climate solutions offer opportunities to restore biodiversity while mitigating climate change. The Bonn Challenge is a U.N. programme to restore biodiversity and mitigate climate change through restoration of the world's degraded landscapes. It provides an unprecedented chance for ecological restoration to become a linchpin tool for addressing many environmental issues. Unfortunately, the Forest and Landscape Restoration programme that underpins the Bonn Challenge, as its name suggests, remains focused on trees and forests, despite rising evidence that many non‐forest ecosystems also offer strong restoration potential for biodiversity and climate mitigation. We see a need for restoration to step back to be more inclusive of different ecosystem types and to step up to provide integrated scientific knowledge to inform large‐scale restoration. Stepping back and up will require assessments of where to restore what species, with recognition that in many landscapes multiple habitat types should be restored. In the process, trade‐offs in the delivery of different ecosystem services (e.g. carbon, biodiversity, water, albedo, livestock forage) should be clearly addressed. We recommend that biodiversity safeguards be included in policy and implemented in practice, to avoid undermining the biophysical relationships that provide ecosystem resilience to climate change. For ecological restoration to contribute to international policy goals will require integrated large‐scale science that works across biome boundaries.     

Trade‐offs between land and water requirements for large‐scale bioenergy production

Bioenergy is expected to play an important role in the future energy mix as it can substitute fossil fuels and contribute to climate change mitigation. However, large‐scale bioenergy cultivation may put substantial pressure on land and water resources. While irrigated bioenergy production can reduce the pressure on land due to higher yields, associated irrigation water requirements may lead to degradation of freshwater ecosystems and to conflicts with other potential users. In this article, we investigate the trade‐offs between land and water requirements of large‐scale bioenergy production. To this end, we adopt an exogenous demand trajectory for bioenergy from dedicated energy crops, targeted at limiting greenhouse gas emissions in the energy sector to 1100 Gt carbon dioxide equivalent until 2095. We then use the spatially explicit global land‐ and water‐use allocation model MAgPIE to project the implications of this bioenergy target for global land and water resources. We find that producing 300 EJ yr^?1 of bioenergy in 2095 from dedicated bioenergy crops is likely to double agricultural water withdrawals if no explicit water protection policies are implemented. Since current human water withdrawals are dominated by agriculture and already lead to ecosystem degradation and biodiversity loss, such a doubling will pose a severe threat to freshwater ecosystems. If irrigated bioenergy production is prohibited to prevent negative impacts of bioenergy cultivation on water resources, bioenergy land requirements for meeting a 300 EJ yr^?1 bioenergy target increase substantially (+ 41%) – mainly at the expense of pasture areas and tropical forests. Thus, avoiding negative environmental impacts of large‐scale bioenergy production will require policies that balance associated water and land requirements.     

造林再造林、森林采伐、气候变化、CO2浓度升高、火灾和虫害对森林固碳能力的影响

森林生态系统具有吸收大气CO_2、缓解气候变化的作用。造林再造林作为京都议定书认可的大气CO_2减排途径,是提高森林固碳能力的低成本、有效策略。森林生态系统固碳能力还受森林采伐、气候变化、大气CO_2浓度升高、火灾以及虫害等自然因素和人为因素的强烈影响。综述了全球和区域造林再造林的固碳能力,以及目前较受重视的一些因素(森林采伐、气候变化、大气CO_2浓度升高、火灾以及虫害)对森林生态系统固碳能力的影响。结果表明,全球造林再造林固碳能力为148—2400TgC/a;采伐造成的全球森林碳损失最大为900 TgC/a,其次是火灾为300 TgC/a,虫害造成森林碳释放最小在2—107 TgC/a之间。建议在今后的研究中,应关注固碳措施和多种环境因素对森林生态系统固碳能力,尤其是对森林土壤固碳能力的影响,严格控制森林采伐和火灾发生,以及减少或避免造林再造林活动引起的碳泄漏。     

Atmospheric impact of bioenergy based on perennial crop (reed canary grass,Phalaris arundinaceae,L.) cultivation on a drained boreal organic soil

Marginal organic soils, abundant in the boreal region, are being increasingly used for bioenergy crop cultivation. Using long‐term field experimental data on greenhouse gas (GHG) balance from a perennial bioenergy crop [reed canary grass (RCG), Phalaris arundinaceae L.] cultivated on a drained organic soil as an example, we show here for the first time that, with a proper cultivation and land‐use practice, environmentally sound bioenergy production is possible on these problematic soil types. We performed a life cycle assessment (LCA) for RCG on this organic soil. We found that, on an average, this system produces 40% less CO₂‐equivalents per MWh of energy in comparison with a conventional energy source such as coal. Climatic conditions regulating the RCG carbon exchange processes have a high impact on the benefits from this bioenergy production system. Under appropriate hydrological conditions, this system can even be carbon‐negative. An LCA sensitivity analysis revealed that net ecosystem CO₂ exchange and crop yield are the major LCA components, while non‐CO₂ GHG emissions and costs associated with crop production are the minor ones. Net bioenergy GHG emissions resulting from restricted net CO₂ uptake and low crop yields, due to climatic and moisture stress during dry years, were comparable with coal emissions. However, net bioenergy emissions during wet years with high net uptake and crop yield were only a third of the coal emissions. As long‐term experimental data on GHG balance of bioenergy production are scarce, scientific data stemming from field experiments are needed in shaping renewable energy source policies.     

Using ecosystem CO2 measurements to estimate the timing and magnitude of greenhouse gas mitigation potential of forest bioenergy

Forest bioenergy opportunities may be hindered by a long greenhouse gas (GHG) payback time. Estimating this payback time requires the quantification of forest‐atmosphere carbon exchanges, usually through process‐based simulation models. Such models are prone to large uncertainties, especially over long‐term carbon fluxes from dead organic matter pools. We propose the use of whole ecosystem field‐measured CO₂ exchanges obtained from eddy covariance flux towers to assess the GHG mitigation potential of forest biomass projects as a way to implicitly integrate all field‐level CO₂ fluxes and the inter‐annual variability in these fluxes. As an example, we perform the evaluation of a theoretical bioenergy project that uses tree stems as bioenergy feedstock and include multi‐year measurements of net ecosystem exchange (NEE) from forest harvest chronosequences in the boreal forest of Canada to estimate the time dynamics of ecosystem CO₂ exchanges following harvesting. Results from this approach are consistent with previous results using process‐based models and suggest a multi‐decadal payback time for our project. The time for atmospheric carbon debt repayment of bioenergy projects is highly dependent on ecosystem‐level CO₂ exchanges. The use of empirical NEE measurements may provide a direct evaluation of, or at least constraints on, the GHG mitigation potential of forest bioenergy projects.     

Assessment of ecosystem resilience to hydroclimatic disturbances in India

Recent studies have shown an increasing trend in hydroclimatic disturbances like droughts, which are anticipated to become more frequent and intense under global warming and climate change. Droughts adversely affect the vegetation growth and crop yield, which enhances the risks to food security for a country like India with over 1.2 billion people to feed. Here, we compared the response of terrestrial net primary productivity (NPP) to hydroclimatic disturbances in India at different scales (i.e., at river basins, land covers, and climate types) to examine the ecosystems’ resilience to such adverse conditions. The ecosystem water use efficiency (WUE_e: NPP/Evapotranspiration) is an effective indicator of ecosystem productivity, linking carbon (C) and water cycles. We found a significant difference (p < .05) in WUE_e across India at different scales. The ecosystem resilience analysis indicated that most of the river basins were not resilient enough to hydroclimatic disturbances. Drastic reduction in WUE_e under dry conditions was observed for some basins, which highlighted the cross‐biome incapability to withstand such conditions. The ecosystem resilience at land cover and climate type scale did not completely relate to the basin‐scale ecosystem resilience, which indicated that ecosystem resilience at basin scale is controlled by some other ecohydrological processes. Our results facilitate the identification of the most sensitive regions in the country for ecosystem management and climate policy making, and highlight the need for taking sufficient adaptation measures to ensure sustainability of ecosystems.     

Conservation of wildlife populations: factoring in incremental disturbance

Progressive anthropogenic disturbance can alter ecosystem organization potentially causing shifts from one stable state to another. This potential for ecosystem shifts must be considered when establishing targets and objectives for conservation. We ask whether a predator–prey system response to incremental anthropogenic disturbance might shift along a disturbance gradient and, if it does, whether any disturbance thresholds are evident for this system. Development of linear corridors in forested areas increases wolf predation effectiveness, while high density of development provides a safe‐haven for their prey. If wolves limit moose population growth, then wolves and moose should respond inversely to land cover disturbance. Using general linear model analysis, we test how the rate of change in moose (Alces alces) density and wolf (Canis lupus) harvest density are influenced by the rate of change in land cover and proportion of land cover disturbed within a 300,000 km² area in the boreal forest of Alberta, Canada. Using logistic regression, we test how the direction of change in moose density is influenced by measures of land cover change. In response to incremental land cover disturbance, moose declines occurred where <43% of land cover was disturbed; in such landscapes, there were high rates of increase in linear disturbance and wolf density increased. By contrast, moose increases occurred where >43% of land cover was disturbed and wolf density declined. Wolves and moose appeared to respond inversely to incremental disturbance with the balance between moose decline and wolf increase shifting at about 43% of land cover disturbed. Conservation decisions require quantification of disturbance rates and their relationships to predator–prey systems because ecosystem responses to anthropogenic disturbance shift across disturbance gradients.     

Patterns in CH4 and CO2 concentrations across boreal rivers: Major drivers and implications for fluvial greenhouse emissions under climate change scenarios

It is now widely accepted that boreal rivers and streams are regionally significant sources of carbon dioxide (CO₂), yet their role as methane (CH₄) emitters, as well as the sensitivity of these greenhouse gas (GHG) emissions to climate change, are still largely undefined. In this study, we explore the large‐scale patterns of fluvial CO₂ and CH₄ partial pressure (pCO₂, pCH₄) and gas exchange (k) relative to a set of key, climate‐sensitive river variables across 46 streams and rivers in two distinct boreal landscapes of Northern Québec. We use the resulting models to determine the direction and magnitude of C‐gas emissions from these boreal fluvial networks under scenarios of climate change. River pCO₂ and pCH₄ were positively correlated, although the latter was two orders of magnitude more variable. We provide evidence that in‐stream metabolism strongly influences the dynamics of surface water pCO₂ and pCH₄, but whereas pCO₂ is not influenced by temperature in the surveyed streams and rivers, pCH₄ appears to be strongly temperature‐dependent. The major predictors of ambient gas concentrations and exchange were water temperature, velocity, and DOC, and the resulting models indicate that total GHG emissions (C‐CO₂ equivalent) from the entire network may increase between by 13 to 68% under plausible scenarios of climate change over the next 50 years. These predicted increases in fluvial GHG emissions are mostly driven by a steep increase in the contribution of CH₄ (from 36 to over 50% of total CO₂‐equivalents). The current role of boreal fluvial networks as major landscape sources of C is thus likely to expand, mainly driven by large increases in fluvial CH₄ emissions.     

Interannual variability in carbon dioxide fluxes and flux–climate relationships on grazed and ungrazed northern mixed-grass prairie

The annual carbon (C) budget of grasslands is highly dynamic, dependent on grazing history and on effects of interannual variability (IAV) in climate on carbon dioxide (CO₂) fluxes. Variability in climatic drivers may directly affect fluxes, but also may indirectly affect fluxes by altering the response of the biota to the environment, an effect termed ‘functional change’. We measured net ecosystem exchange of CO₂ (NEE) and its diurnal components, daytime ecosystem CO₂ exchange (P_D) and night‐time respiration (R_E), on grazed and ungrazed mixed‐grass prairie in North Dakota, USA, for five growing seasons. Our primary objective was to determine how climatic anomalies influence variability in CO₂ exchange. We used regression analysis to distinguish direct effects of IAV in climate on fluxes from functional change. Functional change was quantified as the improvement in regression on fitting a model in which slopes of flux–climate relationships vary among years rather than remain invariant. Functional change and direct effects of climatic variation together explained about 20% of variance in weekly means of NEE, P_D, and R_E. Functional change accounted for more than twice the variance in fluxes of direct effects of climatic variability. Grazing did not consistently influence the contribution of functional change to flux variability, but altered which environmental variable best explained year‐to‐year differences in flux–climate slopes, reduced IAV in seasonal means of fluxes, lessened the strength of flux–climate correlations, and increased NEE by reducing R_E relatively more than P_D. Most of these trends are consistent with the interpretation that grazing reduced the influence of plants on ecosystem fluxes. Because relationships between weekly values of fluxes and climatic regulators changed annually, year‐to‐year differences in the C balance of these ecosystems cannot be predicted from knowledge of IAV in climate alone.     

Abrupt changes in Great Britain vegetation carbon projected under climate change

Past abrupt ‘regime shifts’ have been observed in a range of ecosystems due to various forcing factors. Large‐scale abrupt shifts are projected for some terrestrial ecosystems under climate change, particularly in tropical and high‐latitude regions. However, there is very little high‐resolution modelling of smaller‐scale future projected abrupt shifts in ecosystems, and relatively less focus on the potential for abrupt shifts in temperate terrestrial ecosystems. Here, we show that numerous climate‐driven abrupt shifts in vegetation carbon are projected in a high‐resolution model of Great Britain's land surface driven by two different climate change scenarios. In each scenario, the effects of climate and CO₂ combined are isolated from the effects of climate change alone. We use a new algorithm to detect and classify abrupt shifts in model time series, assessing the sign and strength of the non‐linear responses. The abrupt ecosystem changes projected are non‐linear responses to climate change, not simply driven by abrupt shifts in climate. Depending on the scenario, 374–1,144 grid cells of 1.5 km × 1.5 km each, comprising 0.5%–1.5% of Great Britain's land area show abrupt shifts in vegetation carbon. We find that abrupt ecosystem shifts associated with increases (rather than decreases) in vegetation carbon, show the greatest potential for early warning signals (rising autocorrelation and variance beforehand). In one scenario, 89% of abrupt increases in vegetation carbon show increasing autocorrelation and variance beforehand. Across the scenarios, 81% of abrupt increases in vegetation carbon have increasing autocorrelation and 74% increasing variance beforehand, whereas for decreases in vegetation carbon these figures are 56% and 47% respectively. Our results should not be taken as specific spatial or temporal predictions of abrupt ecosystem change. However, they serve to illustrate that numerous abrupt shifts in temperate terrestrial ecosystems could occur in a changing climate, with some early warning signals detectable beforehand.