High‐resolution spatial modelling of greenhouse gas emissions from land‐use change to energy crops in the United Kingdom

We implemented a spatial application of a previously evaluated model of soil GHG emissions, ECOSSE, in the United Kingdom to examine the impacts to 2050 of land‐use transitions from existing land use, rotational cropland, permanent grassland or woodland, to six bioenergy crops; three ‘first‐generation’ energy crops: oilseed rape, wheat and sugar beet, and three ‘second‐generation’ energy crops: Miscanthus, short rotation coppice willow (SRC) and short rotation forestry poplar (SRF). Conversion of rotational crops to Miscanthus, SRC and SRF and conversion of permanent grass to SRF show beneficial changes in soil GHG balance over a significant area. Conversion of permanent grass to Miscanthus, permanent grass to SRF and forest to SRF shows detrimental changes in soil GHG balance over a significant area. Conversion of permanent grass to wheat, oilseed rape, sugar beet and SRC and all conversions from forest show large detrimental changes in soil GHG balance over most of the United Kingdom, largely due to moving from uncultivated soil to regular cultivation. Differences in net GHG emissions between climate scenarios to 2050 were not significant. Overall, SRF offers the greatest beneficial impact on soil GHG balance. These results provide one criterion for selection of bioenergy crops and do not consider GHG emission increases/decreases resulting from displaced food production, bio‐physical factors (e.g. the energy density of the crop) and socio‐economic factors (e.g. expenditure on harvesting equipment). Given that the soil GHG balance is dominated by change in soil organic carbon (SOC) with the difference among Miscanthus, SRC and SRF largely determined by yield, a target for management of perennial energy crops is to achieve the best possible yield using the most appropriate energy crop and cultivar for the local situation.     

Decoupling of greenhouse gas emissions from global agricultural production: 1970–2050

Since 1970 global agricultural production has more than doubled; contributing ~1/4 of total anthropogenic greenhouse gas (GHG) burden in 2010. Food production must increase to feed our growing demands, but to address climate change, GHG emissions must decrease. Using an identity approach, we estimate and analyse past trends in GHG emission intensities from global agricultural production and land‐use change and project potential future emissions. The novel Kaya–Porter identity framework deconstructs the entity of emissions from a mix of multiple sources of GHGs into attributable elements allowing not only a combined analysis of the total level of all emissions jointly with emissions per unit area and emissions per unit product. It also allows us to examine how a change in emissions from a given source contributes to the change in total emissions over time. We show that agricultural production and GHGs have been steadily decoupled over recent decades. Emissions peaked in 1991 at ~12 Pg CO₂‐eq. yr^?1 and have not exceeded this since. Since 1970 GHG emissions per unit product have declined by 39% and 44% for crop‐ and livestock‐production, respectively. Except for the energy‐use component of farming, emissions from all sources have increased less than agricultural production. Our projected business‐as‐usual range suggests that emissions may be further decoupled by 20–55% giving absolute agricultural emissions of 8.2–14.5 Pg CO₂‐eq. yr^?1 by 2050, significantly lower than many previous estimates that do not allow for decoupling. Beyond this, several additional costcompetitive mitigation measures could reduce emissions further. However, agricultural GHG emissions can only be reduced to a certain level and a simultaneous focus on other parts of the food‐system is necessary to increase food security whilst reducing emissions. The identity approach presented here could be used as a methodological framework for more holistic food systems analysis.     

CO2 emissions from land‐use change affected more by nitrogen cycle,than by the choice of land‐cover data

The high uncertainty in land‐based CO₂ fluxes estimates is thought to be mainly due to uncertainty in not only quantifying historical changes among forests, croplands, and grassland, but also due to different processes included in calculation methods. Inclusion of a nitrogen (N) cycle in models is fairly recent and strongly affects carbon (C) fluxes. In this study, for the first time, we use a model with C and N dynamics with three distinct historical reconstructions of land‐use and land‐use change (LULUC) to quantify LULUC emissions and uncertainty that includes the integrated effects of not only climate and CO₂ but also N. The modeled global average emissions including N dynamics for the 1980s, 1990s, and 2000–2005 were 1.8 ± 0.2, 1.7 ± 0.2, and 1.4 ± 0.2 GtC yr^?1, respectively, (mean and range across LULUC data sets). The emissions from tropics were 0.8 ± 0.2, 0.8 ± 0.2, and 0.7 ± 0.3 GtC yr^?1, and the non tropics were 1.1 ± 0.5, 0.9 ± 0.2, and 0.7 ± 0.1 GtC yr^?1. Compared to previous studies that did not include N dynamics, modeled net LULUC emissions were higher, particularly in the non tropics. In the model, N limitation reduces regrowth rates of vegetation in temperate areas resulting in higher net emissions. Our results indicate that exclusion of N dynamics leads to an underestimation of LULUC emissions by around 70% in the non tropics, 10% in the tropics, and 40% globally in the 1990s. The differences due to inclusion/exclusion of the N cycle of 0.1 GtC yr^?1 in the tropics, 0.6 GtC yr^?1 in the non tropics, and 0.7 GtC yr^?1 globally (mean across land‐cover data sets) in the 1990s were greater than differences due to the land‐cover data in the non tropics and globally (0.2 GtC yr^?1). While land‐cover information is improving with satellite and inventory data, this study indicates the importance of accounting for different processes, in particular the N cycle.     

Temporal response of soil organic carbon after grassland‐related land‐use change

The net flux of CO₂ exchanged with the atmosphere following grassland‐related land‐use change (LUC) depends on the subsequent temporal dynamics of soil organic carbon (SOC). Yet, the magnitude and timing of these dynamics are still unclear. We compiled a global data set of 836 paired‐sites to quantify temporal SOC changes after grassland‐related LUC. In order to discriminate between SOC losses from the initial ecosystem and gains from the secondary one, the post‐LUC time series of SOC data was combined with satellite‐based net primary production observations as a proxy of carbon input to the soil. Globally, land conversion from either cropland or forest into grassland leads to SOC accumulation; the reverse shows net SOC loss. The SOC response curves vary between different regions. Conversion of cropland to managed grassland results in more SOC accumulation than natural grassland recovery from abandoned cropland. We did not consider the biophysical variables (e.g., climate conditions and soil properties) when fitting the SOC turnover rate into the observation data but analyzed the relationships between the fitted turnover rate and these variables. The SOC turnover rate is significantly correlated with temperature and precipitation (p < 0.05), but not with the clay fraction of soils (p > 0.05). Comparing our results with predictions from bookkeeping models, we found that bookkeeping models overestimate by 56% of the long‐term (100 years horizon) cumulative SOC emissions for grassland‐related LUC types in tropical and temperate regions since 2000. We also tested the spatial representativeness of our data set and calculated SOC response curves using the representative subset of sites in each region. Our study provides new insight into the impact grassland‐related LUC on the global carbon budget and sheds light on the potential of grassland conservation for climate mitigation.     

The priming potential of environmentally weathered pyrogenic carbon during land‐use transition to biomass crop production

Since land‐use change (LUC) to lignocellulosic biomass crops often causes a loss of soil organic carbon (SOC), at least in the short term, this study investigated the potential for pyrogenic carbon (PyC) to ameliorate this effect. Although negative priming has been observed in many studies, most of these are long‐term incubation experiments which do not account for the interactions between environmentally weathered PyC and native SOC. Here, the aim was to assess the impact of environmentally weathered PyC on native SOC mineralization at different time points in LUC from arable crops to short rotation coppice (SRC) willow. At eight SRC willow plantations in England, with ages of 3–22 years, soil amended 18–22 months previously with PyC was compared with unamended control soil. Cumulative CO₂ flux was measured weekly from incubated soil at 0–5 cm depth, and soil‐surface CO₂ flux was also measured in the field. For the incubated soil, cumulative CO₂ flux was significantly higher from soil containing weathered PyC than the control soil for seven of the eight sites. Across all sites, the mean cumulative CO₂ flux was 21% higher from soil incubated with weathered PyC than the control soil. These results indicate the potential for positive priming in the surface 5 cm of soil independent of changes in soil properties following LUC to SRC willow production. However, no net effect on CO₂ flux was observed in the field, suggesting this increase in CO₂ is offset by a contrasting PyC‐induced effect at a different soil depth or that different effects were observed under laboratory and field conditions. Although the mechanisms for these contrasting effects remain unclear, results presented here suggest that PyC does not reduce LUC‐induced SOC losses through negative priming, at least for this PyC type and application rate.     

Greenhouse gas mitigation potential in crop production with biochar soil amendment—a carbon footprint assessment for cross‐site field experiments from China

Biochar soil amendment (BSA) had been advocated as a promising approach to mitigate greenhouse gas (GHG) emissions in agriculture. However, the net GHG mitigation potential of BSA remained unquantified with regard to the manufacturing process and field application. Carbon footprint (CF) was employed to assess the mitigating potential of BSA by estimating all the direct and indirect GHG emissions in the full life cycles of crop production including production and field application of biochar. Data were obtained from 7 sites (4 sites for paddy rice production and 3 sites for maize production) under a single BSA at 20 t/ha^?1 across mainland China. Considering soil organic carbon (SOC) sequestration and GHG emission reduction from syngas recycling, BSA reduced the CFs by 20.37–41.29 t carbon dioxide equivalent ha^?1 (CO₂‐eq ha^?1) and 28.58–39.49 t CO₂‐eq ha^?1 for paddy rice and maize production, respectively, compared to no biochar application. Without considering SOC sequestration and syngas recycling, the net CF change by BSA was in a range of ?25.06 to 9.82 t CO₂‐eq ha^?1 and ?20.07 to 5.95 t CO₂‐eq ha^?1 for paddy rice and maize production, respectively, over no biochar application. As the largest contributors among the others, syngas recycling in the process of biochar manufacture contributed by 47% to total CF reductions under BSA for rice cultivation while SOC sequestration contributed by 57% for maize cultivation. There was a large variability of the CF reductions across the studied sites whether in paddy rice or maize production, due likely to the difference in GHG emission reductions and SOC increments under BSA across the sites. This study emphasized that SOC sequestration should be taken into account the CF calculation of BSA. Improved biochar manufacturing technique could achieve a remarkable carbon sink by recycling the biogas for traditional fossil‐fuel replacement.     

Soil carbon sequestration and land‐use change: processes and potential

When agricultural land is no longer used for cultivation and allowed to revert to natural vegetation or replanted to perennial vegetation, soil organic carbon can accumulate. This accumulation process essentially reverses some of the effects responsible for soil organic carbon losses from when the land was converted from perennial vegetation. We discuss the essential elements of what is known about soil organic matter dynamics that may result in enhanced soil carbon sequestration with changes in land‐use and soil management. We review literature that reports changes in soil organic carbon after changes in land‐use that favour carbon accumulation. This data summary provides a guide to approximate rates of SOC sequestration that are possible with management, and indicates the relative importance of some factors that influence the rates of organic carbon sequestration in soil. There is a large variation in the length of time for and the rate at which carbon may accumulate in soil, related to the productivity of the recovering vegetation, physical and biological conditions in the soil, and the past history of soil organic carbon inputs and physical disturbance. Maximum rates of C accumulation during the early aggrading stage of perennial vegetation growth, while substantial, are usually much less than 100 g C m^?2 y^?1. Average rates of accumulation are similar for forest or grassland establishment: 33.8 g C m^?2 y^?1 and 33.2 g C m^?2 y^?1, respectively. These observed rates of soil organic C accumulation, when combined with the small amount of land area involved, are insufficient to account for a significant fraction of the missing C in the global carbon cycle as accumulating in the soils of formerly agricultural land.     

Agricultural peatland restoration: effects of land‐use change on greenhouse gas (CO2 and CH4) fluxes in the Sacramento‐San Joaquin Delta

Agricultural drainage of organic soils has resulted in vast soil subsidence and contributed to increased atmospheric carbon dioxide (CO₂) concentrations. The Sacramento‐San Joaquin Delta in California was drained over a century ago for agriculture and human settlement and has since experienced subsidence rates that are among the highest in the world. It is recognized that drained agriculture in the Delta is unsustainable in the long‐term, and to help reverse subsidence and capture carbon (C) there is an interest in restoring drained agricultural land‐use types to flooded conditions. However, flooding may increase methane (CH₄) emissions. We conducted a full year of simultaneous eddy covariance measurements at two conventional drained agricultural peatlands (a pasture and a corn field) and three flooded land‐use types (a rice paddy and two restored wetlands) to assess the impact of drained to flooded land‐use change on CO₂ and CH₄ fluxes in the Delta. We found that the drained sites were net C and greenhouse gas (GHG) sources, releasing up to 341 g C m^?2 yr^?1 as CO₂ and 11.4 g C m^?2 yr^?1 as CH₄. Conversely, the restored wetlands were net sinks of atmospheric CO₂, sequestering up to 397 g C m^?2 yr^?1. However, they were large sources of CH₄, with emissions ranging from 39 to 53 g C m^?2 yr^?1. In terms of the full GHG budget, the restored wetlands could be either GHG sources or sinks. Although the rice paddy was a small atmospheric CO₂ sink, when considering harvest and CH₄ emissions, it acted as both a C and GHG source. Annual photosynthesis was similar between sites, but flooding at the restored sites inhibited ecosystem respiration, making them net CO₂ sinks. This study suggests that converting drained agricultural peat soils to flooded land‐use types can help reduce or reverse soil subsidence and reduce GHG emissions.     

Soil quality indicator response to land‐use change from annual to perennial bioenergy cropping systems in Germany

Production of biomass feedstock for methanation in Europe has focused on silages of maize and cereals. As ecological awareness has increased in the last several years, more attention is being focused on perennial energy crops (PECs). Studies of specific PECs have shown that their cultivation may enhance agrobiodiversity and increase soil organic carbon stocks while simultaneously providing valuable feedstock for methanation. This study was designed to compare soil quality indicators under annual energy crops (AECs), PECs and permanent grassland (PGL) on the landscape level in south‐western Germany. At a total 25 study sites, covering a wide range of parent materials, the cropping systems were found adjacent to each other. Stands were commercially managed, and PECs included different species such as the Cup Plant, Tall Wheatgrass, Giant Knotweed, Miscanthus, Virginia Mallow and Reed Canary Grass. Soil sampling was carried out for the upper 20 cm of soil. Several soil quality indicators, including soil organic carbon (C_org), soil microbial biomass (C_mic), and aggregate stability, showed that PECs were intermediate between AEC and PGL systems. At landscape level, mean C_org content for (on average) 6.1‐year‐old stands of PEC was 22.37 (±7.53) g kg^?1, compared to 19.23 (±8.08) and 32.08 (±10.11) for AEC and PGL. C_mic contents were higher in PECs (356 ± 241 μg C g^?1) compared to AECs (291 ± 145) but significantly lower than under PGL (753 ± 417). The aggregate stability increased by almost 65% in PECs compared to AEC but was still 57% lower than in PGL. Indicator differences among cropping systems were more pronounced when inherent differences in the parent material were accounted for in the comparisons. Overall, these results suggest that the cultivation of PECs has positive effects on soil quality indicators. Thus, PECs may offer potential to make the production of biomass feedstock more sustainable.     

中国农业系统近40年温室气体排放核算

基于排放因子法构建了包含种植业和牲畜养殖业的农业系统温室气体排放核算体系,系统核算了1980-2020年我国全国尺度上的农业系统温室气体排放总量和变化趋势,并在区县级尺度下对1980、2000、2011年的中国农业系统的温室气体排放量进行核算,对比不同阶段农业系统温室气体排放变化的时空异质性规律。研究发现：1980-2020年我国农业系统温室气体排放量呈波动增长趋势,增长了近46%。CH₄是农业系统排放贡献最大的温室气体,占总排放量的47.33%。我国农业系统温室气体排放与不同地区农业生产方式有关,CH₄排放量高的地区主要位于我国主要水稻产区以及旱地作物产区。CO₂排放量高的地区主要位于东北、西北等地区以及华东地区。N₂O排放量较高地区主要位于西北的主要畜牧养殖地区,以及我国农业经济发展水平高的中南部地区。研究有助于揭示我国农业温室气体排放的动态特征,现状规律,以及空间差异性特征,从农业减排角度为实现双碳目标提供科学参考。     

Conversion of coastal wetlands,riparian wetlands,and peatlands increases greenhouse gas emissions: A global meta‐analysis

Land‐use/land‐cover change (LULCC) often results in degradation of natural wetlands and affects the dynamics of greenhouse gases (GHGs). However, the magnitude of changes in GHG emissions from wetlands undergoing various LULCC types remains unclear. We conducted a global meta‐analysis with a database of 209 sites to examine the effects of LULCC types of constructed wetlands (CWs), croplands (CLs), aquaculture ponds (APs), drained wetlands (DWs), and pastures (PASs) on the variability in CO₂, CH₄, and N₂O emissions from the natural coastal wetlands, riparian wetlands, and peatlands. Our results showed that the natural wetlands were net sinks of atmospheric CO₂ and net sources of CH₄ and N₂O, exhibiting the capacity to mitigate greenhouse effects due to negative comprehensive global warming potentials (GWPs; ?0.9 to ?8.7 t CO₂‐eq ha^?1 year^?1). Relative to the natural wetlands, all LULCC types (except CWs from coastal wetlands) decreased the net CO₂ uptake by 69.7%?456.6%, due to a higher increase in ecosystem respiration relative to slight changes in gross primary production. The CWs and APs significantly increased the CH₄ emissions compared to those of the coastal wetlands. All LULCC types associated with the riparian wetlands significantly decreased the CH₄ emissions. When the peatlands were converted to the PASs, the CH₄ emissions significantly increased. The CLs, as well as DWs from peatlands, significantly increased the N₂O emissions in the natural wetlands. As a result, all LULCC types (except PASs from riparian wetlands) led to remarkably higher GWPs by 65.4%?2,948.8%, compared to those of the natural wetlands. The variability in GHG fluxes with LULCC was mainly sensitive to changes in soil water content, water table, salinity, soil nitrogen content, soil pH, and bulk density. This study highlights the significant role of LULCC in increasing comprehensive GHG emissions from global natural wetlands, and our results are useful for improving future models and manipulative experiments.     

Hotspots of uncertainty in land‐use and land‐cover change projections: a global‐scale model comparison

Model‐based global projections of future land‐use and land‐cover (LULC) change are frequently used in environmental assessments to study the impact of LULC change on environmental services and to provide decision support for policy. These projections are characterized by a high uncertainty in terms of quantity and allocation of projected changes, which can severely impact the results of environmental assessments. In this study, we identify hotspots of uncertainty, based on 43 simulations from 11 global‐scale LULC change models representing a wide range of assumptions of future biophysical and socioeconomic conditions. We attribute components of uncertainty to input data, model structure, scenario storyline and a residual term, based on a regression analysis and analysis of variance. From this diverse set of models and scenarios, we find that the uncertainty varies, depending on the region and the LULC type under consideration. Hotspots of uncertainty appear mainly at the edges of globally important biomes (e.g., boreal and tropical forests). Our results indicate that an important source of uncertainty in forest and pasture areas originates from different input data applied in the models. Cropland, in contrast, is more consistent among the starting conditions, while variation in the projections gradually increases over time due to diverse scenario assumptions and different modeling approaches. Comparisons at the grid cell level indicate that disagreement is mainly related to LULC type definitions and the individual model allocation schemes. We conclude that improving the quality and consistency of observational data utilized in the modeling process and improving the allocation mechanisms of LULC change models remain important challenges. Current LULC representation in environmental assessments might miss the uncertainty arising from the diversity of LULC change modeling approaches, and many studies ignore the uncertainty in LULC projections in assessments of LULC change impacts on climate, water resources or biodiversity.     

Land use efficiency: anticipating future demand for land‐sector greenhouse gas emissions abatement and managing trade‐offs with agriculture,water, and biodiversity

Competition for land is increasing, and policy needs to ensure the efficient supply of multiple ecosystem services from land systems. We modelled the spatially explicit potential future supply of ecosystem services in Australia's intensive agricultural land in response to carbon markets under four global outlooks from 2013 to 2050. We assessed the productive efficiency of greenhouse gas emissions abatement, agricultural production, water resources, and biodiversity services and compared these to production possibility frontiers (PPFs). While interacting commodity markets and carbon markets produced efficient outcomes for agricultural production and emissions abatement, more efficient outcomes were possible for water resources and biodiversity services due to weak price signals. However, when only two objectives were considered as per typical efficiency assessments, efficiency improvements involved significant unintended trade‐offs for the other objectives and incurred substantial opportunity costs. Considering multiple objectives simultaneously enabled the identification of land use arrangements that were efficient over multiple ecosystem services. Efficient land use arrangements could be selected that meet society's preferences for ecosystem service provision from land by adjusting the metric used to combine multiple services. To effectively manage competition for land via land use efficiency, market incentives are needed that effectively price multiple ecosystem services.     

Energy balances and greenhouse gas emissions of palm oil biodiesel in Indonesia

This study presents a cradle‐to‐gate assessment of the energy balances and greenhouse gas (GHG) emissions of Indonesian palm oil biodiesel production, including the stages of land‐use change (LUC), agricultural phase, transportation, milling, biodiesel processing, and comparing the results from different farming systems, including company plantations and smallholder plantations (either out growers or independent growers) in different locations in Kalimantan and Sumatra of Indonesia. The findings demonstrate that there are considerable differences between the farming systems and the locations in net energy yields (43.6–49.2 GJ t^?1 biodiesel yr^?1) as well as GHG emissions (1969.6–5626.4 kg CO_2eq t^?1 biodiesel yr^?1). The output to input ratios are positive in all cases. The largest GHG emissions result from LUC effects, followed by the transesterification, fertilizer production, agricultural production processes, milling, and transportation. Ecosystem carbon payback times range from 11 to 42 years.     

Impact of tropical land‐use change on soil organic carbon stocks – a meta‐analysis

Land‐use changes are the second largest source of human‐induced greenhouse gas emission, mainly due to deforestation in the tropics and subtropics. CO₂ 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.     

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.     

Biogenic vs. geologic carbon emissions and forest biomass energy production

In the current debate over the CO₂ emissions implications of switching from fossil fuel energy sources to include a substantial amount of woody biomass energy, many scientists and policy makers hold the view that emissions from the two sources should not be equated. Their rationale is that the combustion or decay of woody biomass is simply part of the global cycle of biogenic carbon and does not increase the amount of carbon in circulation. This view is frequently presented as justification to implement policies that encourage the substitution of fossil fuel energy sources with biomass. We present the opinion that this is an inappropriate conceptual basis to assess the atmospheric greenhouse gas (GHG) accounting of woody biomass energy generation. While there are many other environmental, social, and economic reasons to move to woody biomass energy, we argue that the inferred benefits of biogenic emissions over fossil fuel emissions should be reconsidered.     

Effect of land‐use and land‐cover change on mangrove blue carbon: A systematic review

Mangroves shift from carbon sinks to sources when affected by anthropogenic land‐use and land‐cover change (LULCC). Yet, the magnitude and temporal scale of these impacts are largely unknown. We undertook a systematic review to examine the influence of LULCC on mangrove carbon stocks and soil greenhouse gas (GHG) effluxes. A search of 478 data points from the peer‐reviewed literature revealed a substantial reduction of biomass (82% ± 35%) and soil (54% ± 13%) carbon stocks due to LULCC. The relative loss depended on LULCC type, time since LULCC and geographical and climatic conditions of sites. We also observed that the loss of soil carbon stocks was linked to the decreased soil carbon content and increased soil bulk density over the first 100 cm depth. We found no significant effect of LULCC on soil GHG effluxes. Regeneration efforts (i.e. restoration, rehabilitation and afforestation) led to biomass recovery after ~40 years. However, we found no clear patterns of mangrove soil carbon stock re‐establishment following biomass recovery. Our findings suggest that regeneration may help restore carbon stocks back to pre‐disturbed levels over decadal to century time scales only, with a faster rate for biomass recovery than for soil carbon stocks. Therefore, improved mangrove ecosystem management by preventing further LULCC and promoting rehabilitation is fundamental for effective climate change mitigation policy.     

Downscaling land‐use data to provide global 30″ estimates of five land‐use classes

Land‐use change is one of the biggest threats to biodiversity globally. The effects of land use on biodiversity manifest primarily at local scales which are not captured by the coarse spatial grain of current global land‐use mapping. Assessments of land‐use impacts on biodiversity across large spatial extents require data at a similar spatial grain to the ecological processes they are assessing. Here, we develop a method for statistically downscaling mapped land‐use data that combines generalized additive modeling and constrained optimization. This method was applied to the 0.5° Land‐use Harmonization data for the year 2005 to produce global 30″ (approx. 1 km²) estimates of five land‐use classes: primary habitat, secondary habitat, cropland, pasture, and urban. The original dataset was partitioned into 61 bio‐realms (unique combinations of biome and biogeographical realm) and downscaled using relationships with fine‐grained climate, land cover, landform, and anthropogenic influence layers. The downscaled land‐use data were validated using the PREDICTS database and the geoWiki global cropland dataset. Application of the new method to all 61 bio‐realms produced global fine‐grained layers from the 2005 time step of the Land‐use Harmonization dataset. Coarse‐scaled proportions of land use estimated from these data compared well with those estimated in the original datasets (mean R²: 0.68 ± 0.19). Validation with the PREDICTS database showed the new downscaled land‐use layers improved discrimination of all five classes at PREDICTS sites (P < 0.0001 in all cases). Additional validation of the downscaled cropping layer with the geoWiki layer showed an R² improvement of 0.12 compared with the Land‐use Harmonization data. The downscaling method presented here produced the first global land‐use dataset at a spatial grain relevant to ecological processes that drive changes in biodiversity over space and time. Integrating these data with biodiversity measures will enable the reporting of land‐use impacts on biodiversity at a finer resolution than previously possible. Furthermore, the general method presented here could be useful to others wishing to downscale similarly constrained coarse‐resolution data for other environmental variables.     

Bioenergy production and Skylark (Alauda arvensis) population abundance – a modelling approach for the analysis of land‐use change impacts and conservation options

Bioenergy production is seen as one way of meeting future energy needs. The growing demand for biomass for energy production induces the cultivation of a few fast growing and high‐yielding energy crops on vast areas of arable land. This land‐use change has been found associated with the reduction of habitat suitability for farmland birds and a decline in farmland biodiversity in general. A large number of studies have assessed the ecological effects of energy crop cultivation at the local scale of a single field. This study focuses on regional landscape changes caused by increased energy crop cultivation, which includes reduction of crop‐type richness and spatial concentration of single crop‐types. We present a spatially explicit ecological model to assess the population‐level consequences of these effects on the abundance of the farmland bird species Skylark (Alauda arvensis). We also investigate the impacts of different land‐use scenarios and aim to identify adaptive conservation options. We show that (1) the impacts of increased energy crop cultivation on Skylark population abundance depend strongly on the landscape structure; (2) impacts could be tolerated as long as a certain minimum level of crop‐type heterogeneity is retained at the landscape level and (3) conservation actions are required and effective especially on landscapes where crop‐field size is large.