Terrestrial carbon stock mapping is important for the successful implementation of climate change mitigation policies. Its accuracy depends on the availability of reliable allometric models to infer oven‐dry aboveground biomass of trees from census data. The degree of uncertainty associated with previously published pantropical aboveground biomass allometries is large. We analyzed a global database of directly harvested trees at 58 sites, spanning a wide range of climatic conditions and vegetation types (4004 trees ≥ 5 cm trunk diameter). When trunk diameter, total tree height, and wood specific gravity were included in the aboveground biomass model as covariates, a single model was found to hold across tropical vegetation types, with no detectable effect of region or environmental factors. The mean percent bias and variance of this model was only slightly higher than that of locally fitted models. Wood specific gravity was an important predictor of aboveground biomass, especially when including a much broader range of vegetation types than previous studies. The generic tree diameter–height relationship depended linearly on a bioclimatic stress variable E , which compounds indices of temperature variability, precipitation variability, and drought intensity. For cases in which total tree height is unavailable for aboveground biomass estimation, a pantropical model incorporating wood density, trunk diameter, and the variable E outperformed previously published models without height. However, to minimize bias, the development of locally derived diameter–height relationships is advised whenever possible. Both new allometric models should contribute to improve the accuracy of biomass assessment protocols in tropical vegetation types, and to advancing our understanding of architectural and evolutionary constraints on woody plant development.
Ocean acidification represents a threat to marine species worldwide, and forecasting the ecological impacts of acidification is a high priority for science, management, and policy. As research on the topic expands at an exponential rate, a comprehensive understanding of the variability in organisms' responses and corresponding levels of certainty is necessary to forecast the ecological effects. Here, we perform the most comprehensive meta‐analysis to date by synthesizing the results of 228 studies examining biological responses to ocean acidification. The results reveal decreased survival, calcification, growth, development and abundance in response to acidification when the broad range of marine organisms is pooled together. However, the magnitude of these responses varies among taxonomic groups, suggesting there is some predictable trait‐based variation in sensitivity, despite the investigation of approximately 100 new species in recent research. The results also reveal an enhanced sensitivity of mollusk larvae, but suggest that an enhanced sensitivity of early life history stages is not universal across all taxonomic groups. In addition, the variability in species' responses is enhanced when they are exposed to acidification in multi‐species assemblages, suggesting that it is important to consider indirect effects and exercise caution when forecasting abundance patterns from single‐species laboratory experiments. Furthermore, the results suggest that other factors, such as nutritional status or source population, could cause substantial variation in organisms' responses. Last, the results highlight a trend towards enhanced sensitivity to acidification when taxa are concurrently exposed to elevated seawater temperature.
Evolutionary responses are required for tree populations to be able to track climate change. Results of 250 years of common garden experiments show that most forest trees have evolved local adaptation, as evidenced by the adaptive differentiation of populations in quantitative traits, reflecting environmental conditions of population origins. On the basis of the patterns of quantitative variation for 19 adaptation‐related traits studied in 59 tree species (mostly temperate and boreal species from the Northern hemisphere), we found that genetic differentiation between populations and clinal variation along environmental gradients were very common (respectively, 90% and 78% of cases). Thus, responding to climate change will likely require that the quantitative traits of populations again match their environments. We examine what kind of information is needed for evaluating the potential to respond, and what information is already available. We review the genetic models related to selection responses, and what is known currently about the genetic basis of the traits. We address special problems to be found at the range margins, and highlight the need for more modeling to understand specific issues at southern and northern margins. We need new common garden experiments for less known species. For extensively studied species, new experiments are needed outside the current ranges. Improving genomic information will allow better prediction of responses. Competitive and other interactions within species and interactions between species deserve more consideration. Despite the long generation times, the strong background in quantitative genetics and growing genomic resources make forest trees useful species for climate change research. The greatest adaptive response is expected when populations are large, have high genetic variability, selection is strong, and there is ecological opportunity for establishment of better adapted genotypes.
The decomposition and transformation of above‐ and below‐ground plant detritus (litter) is the main process by which soil organic matter ( SOM ) is formed. Yet, research on litter decay and SOM formation has been largely uncoupled, failing to provide an effective nexus between these two fundamental processes for carbon (C) and nitrogen (N) cycling and storage. We present the current understanding of the importance of microbial substrate use efficiency and C and N allocation in controlling the proportion of plant‐derived C and N that is incorporated into SOM , and of soil matrix interactions in controlling SOM stabilization. We synthesize this understanding into the Microbial Efficiency‐Matrix Stabilization ( MEMS ) framework. This framework leads to the hypothesis that labile plant constituents are the dominant source of microbial products, relative to input rates, because they are utilized more efficiently by microbes. These microbial products of decomposition would thus become the main precursors of stable SOM by promoting aggregation and through strong chemical bonding to the mineral soil matrix.
Plant traits - the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs - determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world's 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and persistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation - but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.
Mechanisms to mitigate global climate change by sequestering carbon ( C ) in different ‘sinks' have been proposed as at least temporary measures. Of the major global C pools, terrestrial ecosystems hold the potential to capture and store substantially increased volumes of C in soil organic matter ( SOM ) through changes in management that are also of benefit to the multitude of ecosystem services that soils provide. This potential can only be realized by determining the amount of SOM stored in soils now, with subsequent quantification of how this is affected by management strategies intended to increase SOM concentrations, and used in soil C models for the prediction of the roles of soils in future climate change. An apparently obvious method to increase C stocks in soils is to augment the soil C pools with the longest mean residence times ( MRT ). Computer simulation models of soil C dynamics, e.g. RothC and Century, partition these refractory constituents into slow and passive pools with MRT s of centuries to millennia. This partitioning is assumed to reflect: (i) the average biomolecular properties of SOM in the pools with reference to their source in plant litter, (ii) the accessibility of the SOM to decomposer organisms or catalytic enzymes, or (iii) constraints imposed on decomposition by environmental conditions, including soil moisture and temperature. However, contemporary analytical approaches suggest that the chemical composition of these pools is not necessarily predictable because, despite considerable progress with understanding decomposition processes and the role of decomposer organisms, along with refinements in simulation models, little progress has been made in reconciling biochemical properties with the kinetically defined pools. In this review, we will explore how advances in quantitative analytical techniques have redefined the new understanding of SOM dynamics and how this is affecting the development and application of new modelling approaches to soil C .
The response of soil organic matter ( OM ) decomposition to increasing temperature is a critical aspect of ecosystem responses to global change. The impacts of climate warming on decomposition dynamics have not been resolved due to apparently contradictory results from field and lab experiments, most of which has focused on labile carbon with short turnover times. But the majority of total soil carbon stocks are comprised of organic carbon with turnover times of decades to centuries. Understanding the response of these carbon pools to climate change is essential for forecasting longer‐term changes in soil carbon storage. Herein, we briefly synthesize information from recent studies that have been conducted using a wide variety of approaches. In our effort to understand research to‐date, we derive a new conceptual model that explicitly identifies the processes controlling soil OM availability for decomposition and allows a more explicit description of the factors regulating OM decomposition under different circumstances. It explicitly defines resistance of soil OM to decomposition as being due either to its chemical conformation ( quality ) or its physico‐chemical protection from decomposition. The former is embodied in the depolymerization process, the latter by adsorption/desorption and aggregate turnover. We hypothesize a strong role for variation in temperature sensitivity as a function of reaction rates for both. We conclude that important advances in understanding the temperature response of the processes that control substrate availability, depolymerization, microbial efficiency, and enzyme production will be needed to predict the fate of soil carbon stocks in a warmer world.
With the growing body of literature assessing the impact of invasive alien plants on resident species and ecosystems, a comprehensive assessment of the relationship between invasive species traits and environmental settings of invasion on the characteristics of impacts is needed. Based on 287 publications with 1551 individual cases that addressed the impact of 167 invasive plant species belonging to 49 families, we present the first global overview of frequencies of significant and non‐significant ecological impacts and their directions on 15 outcomes related to the responses of resident populations, species, communities and ecosystems. Species and community outcomes tend to decline following invasions, especially those for plants, but the abundance and richness of the soil biota, as well as concentrations of soil nutrients and water, more often increase than decrease following invasion. Data mining tools revealed that invasive plants exert consistent significant impacts on some outcomes (survival of resident biota, activity of resident animals, resident community productivity, mineral and nutrient content in plant tissues, and fire frequency and intensity), whereas for outcomes at the community level, such as species richness, diversity and soil resources, the significance of impacts is determined by interactions between species traits and the biome invaded. The latter outcomes are most likely to be impacted by annual grasses, and by wind pollinated trees invading mediterranean or tropical biomes. One of the clearest signals in this analysis is that invasive plants are far more likely to cause significant impacts on resident plant and animal richness on islands rather than mainland. This study shows that there is no universal measure of impact and the pattern observed depends on the ecological measure examined. Although impact is strongly context dependent, some species traits, especially life form, stature and pollination syndrome, may provide a means to predict impact, regardless of the particular habitat and geographical region invaded.
Potential consequences of climate change on crop production can be studied using mechanistic crop simulation models. While a broad variety of maize simulation models exist, it is not known whether different models diverge on grain yield responses to changes in climatic factors, or whether they agree in their general trends related to phenology, growth, and yield. With the goal of analyzing the sensitivity of simulated yields to changes in temperature and atmospheric carbon dioxide concentrations [CO2], we present the largest maize crop model intercomparison to date, including 23 different models. These models were evaluated for four locations representing a wide range of maize production conditions in the world: Lusignan (France), Ames (USA), Rio Verde (Brazil) and Morogoro (Tanzania). While individual models differed considerably in absolute yield simulation at the four sites, an ensemble of a minimum number of models was able to simulate absolute yields accurately at the four sites even with low data for calibration, thus suggesting that using an ensemble of models has merit. Temperature increase had strong negative influence on modeled yield response of roughly -0.5 Mg ha-1 per °C. Doubling [CO2] from 360 to 720 µmol mol-1 increased grain yield by 7.5% on average across models and the sites. That would therefore make temperature the main factor altering maize yields at the end of this century. Furthermore, there was a large uncertainty in the yield response to [CO2] among models. Model responses to temperature and [CO2] did not differ whether models were simulated with low calibration information or, simulated with high level of calibration information.
The purpose of this study was to evaluate 10 process‐based terrestrial biosphere models that were used for the IPCC fifth Assessment Report. The simulated gross primary productivity ( GPP ) is compared with flux‐tower‐based estimates by Jung et al . [ Journal of Geophysical Research 116 (2011) G00J07] ( JU 11). The net primary productivity ( NPP ) apparent sensitivity to climate variability and atmospheric CO 2 trends is diagnosed from each model output, using statistical functions. The temperature sensitivity is compared against ecosystem field warming experiments results. The CO 2 sensitivity of NPP is compared to the results from four Free‐Air CO 2 Enrichment ( FACE ) experiments. The simulated global net biome productivity ( NBP ) is compared with the residual land sink ( RLS ) of the global carbon budget from Friedlingstein et al . [ Nature Geoscience 3 (2010) 811] ( FR 10). We found that models produce a higher GPP (133 ± 15 Pg C yr −1 ) than JU 11 (118 ± 6 Pg C yr −1 ). In response to rising atmospheric CO 2 concentration, modeled NPP increases on average by 16% (5–20%) per 100 ppm, a slightly larger apparent sensitivity of NPP to CO 2 than that measured at the FACE experiment locations (13% per 100 ppm). Global NBP differs markedly among individual models, although the mean value of 2.0 ± 0.8 Pg C yr −1 is remarkably close to the mean value of RLS (2.1 ± 1.2 Pg C yr −1 ). The interannual variability in modeled NBP is significantly correlated with that of RLS for the period 1980–2009. Both model‐to‐model and interannual variation in model GPP is larger than that in model NBP due to the strong coupling causing a positive correlation between ecosystem respiration and GPP in the model. The average linear regression slope of global NBP vs. temperature across the 10 models is −3.0 ± 1.5 Pg C yr −1 °C −1 , within the uncertainty of what derived from RLS (−3.9 ± 1.1 Pg C yr −1 °C −1 ). However, 9 of 10 models overestimate the regression slope of NBP vs. precipitation, compared with the slope of the observed RLS vs. precipitation. With most models lacking processes that control GPP and NBP in addition to CO 2 and climate, the agreement between modeled and observation‐based GPP and NBP can be fortuitous. Carbon–nitrogen interactions (only separable in one model) significantly influence the simulated response of carbon cycle to temperature and atmospheric CO 2 concentration, suggesting that nutrients limitations should be included in the next generation of terrestrial biosphere models.
Ecosystems worldwide are receiving increasing amounts of reactive nitrogen ( N ) via anthropogenic activities with the added N having potentially important impacts on microbially mediated belowground carbon dynamics. However, a comprehensive understanding of how elevated N availability affects soil microbial processes and community dynamics remains incomplete. The mechanisms responsible for the observed responses are poorly resolved and we do not know if soil microbial communities respond in a similar manner across ecosystems. We collected 28 soils from a broad range of ecosystems in N orth A merica, amended soils with inorganic N , and incubated the soils under controlled conditions for 1 year. Consistent across nearly all soils, N addition decreased microbial respiration rates, with an average decrease of 11% over the year‐long incubation, and decreased microbial biomass by 35%. High‐throughput pyrosequencing showed that N addition consistently altered bacterial community composition, increasing the relative abundance of A ctinobacteria and F irmicutes , and decreasing the relative abundance of A cidobacteria and V errucomicrobia . Further, N ‐amended soils consistently had lower activities in a broad suite of extracellular enzymes and had decreased temperature sensitivity, suggesting a shift to the preferential decomposition of more labile C pools. The observed trends held across strong gradients in climate and soil characteristics, indicating that the soil microbial responses to N addition are likely controlled by similar wide‐spread mechanisms. Our results support the hypothesis that N addition depresses soil microbial activity by shifting the metabolic capabilities of soil bacterial communities, yielding communities that are less capable of decomposing more recalcitrant soil carbon pools and leading to a potential increase in soil carbon sequestration rates.
Although seagrasses and marine macroalgae (macro‐autotrophs) play critical ecological roles in reef, lagoon, coastal and open‐water ecosystems, their response to ocean acidification ( OA ) and climate change is not well understood. In this review, we examine marine macro‐autotroph biochemistry and physiology relevant to their response to elevated dissolved inorganic carbon [ DIC ], carbon dioxide [ CO 2 ], and lower carbonate [ CO 3 2− ] and pH . We also explore the effects of increasing temperature under climate change and the interactions of elevated temperature and [ CO 2 ]. Finally, recommendations are made for future research based on this synthesis. A literature review of >100 species revealed that marine macro‐autotroph photosynthesis is overwhelmingly C 3 (≥ 85%) with most species capable of utilizing HCO 3 − ; however, most are not saturated at current ocean [ DIC ]. These results, and the presence of CO 2 ‐only users, lead us to conclude that photosynthetic and growth rates of marine macro‐autotrophs are likely to increase under elevated [ CO 2 ] similar to terrestrial C 3 species. In the tropics, many species live close to their thermal limits and will have to up‐regulate stress‐response systems to tolerate sublethal temperature exposures with climate change, whereas elevated [ CO 2 ] effects on thermal acclimation are unknown. Fundamental linkages between elevated [ CO 2 ] and temperature on photorespiration, enzyme systems, carbohydrate production, and calcification dictate the need to consider these two parameters simultaneously. Relevant to calcifiers, elevated [ CO 2 ] lowers net calcification and this effect is amplified by high temperature. Although the mechanisms are not clear, OA likely disrupts diffusion and transport systems of H + and DIC . These fluxes control micro‐environments that promote calcification over dissolution and may be more important than CaCO 3 mineralogy in predicting macroalgal responses to OA . Calcareous macroalgae are highly vulnerable to OA , and it is likely that fleshy macroalgae will dominate in a higher CO 2 ocean; therefore, it is critical to elucidate the research gaps identified in this review.
We combined two existing datasets of vegetation aboveground biomass (AGB) (Proceedings of the National Academy of Sciences of the United States of America, 108, 2011, 9899; Nature Climate Change, 2, 2012, 182) into a pan-tropical AGB map at 1-km resolution using an independent reference dataset of field observations and locally calibrated high-resolution biomass maps, harmonized and upscaled to 14 477 1-km AGB estimates. Our data fusion approach uses bias removal and weighted linear averaging that incorporates and spatializes the biomass patterns indicated by the reference data. The method was applied independently in areas (strata) with homogeneous error patterns of the input (Saatchi and Baccini) maps, which were estimated from the reference data and additional covariates. Based on the fused map, we estimated AGB stock for the tropics (23.4 N–23.4 S) of 375 Pg dry mass, 9–18% lower than the Saatchi and Baccini estimates. The fused map also showed differing spatial patterns of AGB over large areas, with higher AGB density in the dense forest areas in the Congo basin, Eastern Amazon and South-East Asia, and lower values in Central America and in most dry vegetation areas of Africa than either of the input maps. The validation exercise, based on 2118 estimates from the reference dataset not used in the fusion process, showed that the fused map had a RMSE 15–21% lower than that of the input maps and, most importantly, nearly unbiased estimates (mean bias 5 Mg dry mass ha−1 vs. 21 and 28 Mg ha−1 for the input maps). The fusion method can be applied at any scale including the policy-relevant national level, where it can provide improved biomass estimates by integrating existing regional biomass maps as input maps and additional, country-specific reference datasets.
Global mean temperature is predicted to increase by 2–7 °C and precipitation to change across the globe by the end of this century. To quantify climate effects on ecosystem processes, a number of climate change experiments have been established around the world in various ecosystems. Despite these efforts, general responses of terrestrial ecosystems to changes in temperature and precipitation, and especially to their combined effects, remain unclear. We used meta‐analysis to synthesize ecosystem‐level responses to warming, altered precipitation, and their combination. We focused on plant growth and ecosystem carbon (C) balance, including biomass, net primary production (NPP), respiration, net ecosystem exchange (NEE), and ecosystem photosynthesis, synthesizing results from 85 studies. We found that experimental warming and increased precipitation generally stimulated plant growth and ecosystem C fluxes, whereas decreased precipitation had the opposite effects. For example, warming significantly stimulated total NPP, increased ecosystem photosynthesis, and ecosystem respiration. Experimentally reduced precipitation suppressed aboveground NPP (ANPP) and NEE, whereas supplemental precipitation enhanced ANPP and NEE. Plant productivity and ecosystem C fluxes generally showed higher sensitivities to increased precipitation than to decreased precipitation. Interactive effects of warming and altered precipitation tended to be smaller than expected from additive, single‐factor effects, though low statistical power limits the strength of these conclusions. New experiments with combined temperature and precipitation manipulations are needed to conclusively determine the importance of temperature–precipitation interactions on the C balance of terrestrial ecosystems under future climate conditions.
We estimate changes in forest cover (deforestation and forest regrowth) in the tropics for the two last decades (1990–2000 and 2000–2010) based on a sample of 4000 units of 10 ×10 km size. Forest cover is interpreted from satellite imagery at 30 × 30 m resolution. Forest cover changes are then combined with pan‐tropical biomass maps to estimate carbon losses. We show that there was a gross loss of tropical forests of 8.0 million ha yr −1 in the 1990s and 7.6 million ha yr −1 in the 2000s (0.49% annual rate), with no statistically significant difference. Humid forests account for 64% of the total forest cover in 2010 and 54% of the net forest loss during second study decade. Losses of forest cover and Other Wooded Land (OWL) cover result in estimates of carbon losses which are similar for 1990s and 2000s at 887 MtC yr −1 (range: 646–1238) and 880 MtC yr −1 (range: 602–1237) respectively, with humid regions contributing two‐thirds. The estimates of forest area changes have small statistical standard errors due to large sample size. We also reduce uncertainties of previous estimates of carbon losses and removals. Our estimates of forest area change are significantly lower as compared to national survey data. We reconcile recent low estimates of carbon emissions from tropical deforestation for early 2000s and show that carbon loss rates did not change between the two last decades. Carbon losses from deforestation represent circa 10% of Carbon emissions from fossil fuel combustion and cement production during the last decade (2000–2010). Our estimates of annual removals of carbon from forest regrowth at 115 MtC yr −1 (range: 61–168) and 97 MtC yr −1 (53–141) for the 1990s and 2000s respectively are five to fifteen times lower than earlier published estimates.
A new 1 km global IIASA ‐ IFPRI cropland percentage map for the baseline year 2005 has been developed which integrates a number of individual cropland maps at global to regional to national scales. The individual map products include existing global land cover maps such as GlobCover 2005 and MODIS v.5, regional maps such as AFRICOVER and national maps from mapping agencies and other organizations. The different products are ranked at the national level using crowdsourced data from Geo‐Wiki to create a map that reflects the likelihood of cropland. Calibration with national and subnational crop statistics was then undertaken to distribute the cropland within each country and subnational unit. The new IIASA ‐ IFPRI cropland product has been validated using very high‐resolution satellite imagery via Geo‐Wiki and has an overall accuracy of 82.4%. It has also been compared with the EarthStat cropland product and shows a lower root mean square error on an independent data set collected from Geo‐Wiki. The first ever global field size map was produced at the same resolution as the IIASA ‐ IFPRI cropland map based on interpolation of field size data collected via a Geo‐Wiki crowdsourcing campaign. A validation exercise of the global field size map revealed satisfactory agreement with control data, particularly given the relatively modest size of the field size data set used to create the map. Both are critical inputs to global agricultural monitoring in the frame of GEOGLAM and will serve the global land modelling and integrated assessment community, in particular for improving land use models that require baseline cropland information. These products are freely available for downloading from the http://cropland.geo-wiki.org website.
Land‐use changes are the second largest source of human‐induced greenhouse gas emission, mainly due to deforestation in the tropics and subtropics. CO 2 emissions result from biomass and soil organic carbon (SOC) losses and may be offset with afforestation programs. However, the effect of land‐use changes on SOC is poorly quantified due to insufficient data quality (only SOC concentrations and no SOC stocks, shallow sampling depth) and representativeness. In a global meta‐analysis, 385 studies on land‐use change in the tropics were explored to estimate the SOC stock changes for all major land‐use change types. The highest SOC losses were caused by conversion of primary forest into cropland (−25%) and perennial crops (−30%) but forest conversion into grassland also reduced SOC stocks by 12%. Secondary forests stored less SOC than primary forests (−9%) underlining the importance of primary forests for C stores. SOC losses are partly reversible if agricultural land is afforested (+29%) or under cropland fallow (+32%) and with cropland conversion into grassland (+26%). Data on soil bulk density are critical in order to estimate SOC stock changes because (i) the bulk density changes with land‐use and needs to be accounted for when calculating SOC stocks and (ii) soil sample mass has to be corrected for bulk density changes in order to compare land‐use types on the same basis of soil mass. Without soil mass correction, land‐use change effects would have been underestimated by 28%. Land‐use change impact on SOC was not restricted to the surface soil, but relative changes were equally high in the subsoil, stressing the importance of sufficiently deep sampling.
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 C hina, 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) 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 (conifer < broadleaf, evergreen < deciduous 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.
Feeding 9–10 billion people by 2050 and preventing dangerous climate change are two of the greatest challenges facing humanity. Both challenges must be met while reducing the impact of land management on ecosystem services that deliver vital goods and services, and support human health and well‐being. Few studies to date have considered the interactions between these challenges. In this study we briefly outline the challenges, review the supply‐ and demand‐side climate mitigation potential available in the Agriculture, Forestry and Other Land Use AFOLU sector and options for delivering food security. We briefly outline some of the synergies and trade‐offs afforded by mitigation practices, before presenting an assessment of the mitigation potential possible in the AFOLU sector under possible future scenarios in which demand‐side measures codeliver to aid food security. We conclude that while supply‐side mitigation measures, such as changes in land management, might either enhance or negatively impact food security, demand‐side mitigation measures, such as reduced waste or demand for livestock products, should benefit both food security and greenhouse gas ( GHG ) mitigation. Demand‐side measures offer a greater potential (1.5–15.6 Gt CO 2 ‐eq. yr −1 ) in meeting both challenges than do supply‐side measures (1.5–4.3 Gt CO 2 ‐eq. yr −1 at carbon prices between 20 and 100 US$ t CO 2 ‐eq. yr −1 ), but given the enormity of challenges, all options need to be considered. Supply‐side measures should be implemented immediately, focussing on those that allow the production of more agricultural product per unit of input. For demand‐side measures, given the difficulties in their implementation and lag in their effectiveness, policy should be introduced quickly, and should aim to codeliver to other policy agenda, such as improving environmental quality or improving dietary health. These problems facing humanity in the 21st Century are extremely challenging, and policy that addresses multiple objectives is required now more than ever.
The increasing input of anthropogenically derived nitrogen (N) to ecosystems raises a crucial question: how does available N modify the decomposer community and thus affects the mineralization of soil organic matter ( SOM ). Moreover, N input modifies the priming effect ( PE ), that is, the effect of fresh organics on the microbial decomposition of SOM . We studied the interactive effects of C and N on SOM mineralization (by natural 13 C labelling adding C 4 ‐sucrose or C 4 ‐maize straw to C 3 ‐soil) in relation to microbial growth kinetics and to the activities of five hydrolytic enzymes. This encompasses the groups of parameters governing two mechanisms of priming effects – microbial N mining and stoichiometric decomposition theories. In sole C treatments, positive PE was accompanied by a decrease in specific microbial growth rates, confirming a greater contribution of K‐strategists to the decomposition of native SOM . Sucrose addition with N significantly accelerated mineralization of native SOM , whereas mineral N added with plant residues accelerated decomposition of plant residues. This supports the microbial mining theory in terms of N limitation. Sucrose addition with N was accompanied by accelerated microbial growth, increased activities of β ‐glucosidase and cellobiohydrolase, and decreased activities of xylanase and leucine amino peptidase. This indicated an increased contribution of r‐strategists to the PE and to decomposition of cellulose but the decreased hemicellulolytic and proteolytic activities. Thus, the acceleration of the C cycle was primed by exogenous organic C and was controlled by N. This confirms the stoichiometric decomposition theory. Both K‐ and r‐strategists were beneficial for priming effects, with an increasing contribution of K‐selected species under N limitation. Thus, the priming phenomenon described in ‘microbial N mining’ theory can be ascribed to K‐strategists. In contrast, ‘stoichiometric decomposition’ theory, that is, accelerated OM mineralization due to balanced microbial growth, is explained by domination of r‐strategists.