A Land System representation for global assessments and land‐use modeling

Current global scale land‐change models used for integrated assessments and climate modeling are based on classifications of land cover. However, land‐use management intensity and livestock keeping are also important aspects of land use, and are an integrated part of land systems. This article aims to classify, map, and to characterize Land Systems (LS) at a global scale and analyze the spatial determinants of these systems. Besides proposing such a classification, the article tests if global assessments can be based on globally uniform allocation rules. Land cover, livestock, and agricultural intensity data are used to map LS using a hierarchical classification method. Logistic regressions are used to analyze variation in spatial determinants of LS. The analysis of the spatial determinants of LS indicates strong associations between LS and a range of socioeconomic and biophysical indicators of human‐environment interactions. The set of identified spatial determinants of a LS differs among regions and scales, especially for (mosaic) cropland systems, grassland systems with livestock, and settlements. (Semi‐)Natural LS have more similar spatial determinants across regions and scales. Using LS in global models is expected to result in a more accurate representation of land use capturing important aspects of land systems and land architecture: the variation in land cover and the link between land‐use intensity and landscape composition. Because the set of most important spatial determinants of LS varies among regions and scales, land‐change models that include the human drivers of land change are best parameterized at sub‐global level, where similar biophysical, socioeconomic and cultural conditions prevail in the specific regions.     

Anthropogenic disturbance and streams: land use and land‐use change affect stream ecosystems via multiple pathways

1. Ecosystems are strongly influenced by land use practices. However, identifying the mechanisms behind these influences is complicated by the many potential pathways (often indirect) between land use and ecosystems and by the long‐lasting effects of past land use. To support ecosystem restoration and conservation efforts, we need to better understand these indirect and lasting effects. 2. We constructed structural equation models (SEM) to evaluate the direct and indirect effects of contemporary (2002) land use (agriculture and development) and change in land use from 1952 to 2002 on present‐day streams (n = 190) in Maryland, U.S.A. Additional variables examined included site location, system size, altitude, per cent sand in soils, riparian condition, habitat quality, stream water NO₃‐N and benthic macroinvertebrate and fish measures of stream condition. Our first SEM (2002 Land Use) included the proportions of contemporary agriculture and development in catchments in the model. The second SEM (Land Use Change) included five measures of land use change (proportion agricultural in both times, developed in both times, agricultural in 1952 and developed in 2002, forested in 1952 and developed in 2002 and agricultural in 1952 and forested in 2002). 3. The data set fit both SEMs well. The 2002 Land Use model explained 71% of variation in NO₃‐N and 55%, 42% and 38% of variation in riffle quality, macroinvertebrate condition and fish condition, respectively. The Land Use Change model explained similar amounts of variation in NO₃‐N (R² = 0.72), riffle quality (R² = 0.57) and macroinvertebrate condition (R² = 0.44) but slightly more variation in fish condition (R² = 0.43). 4. Both models identified pathways through which landscape variables affect stream responses, including negative direct effects of latitude on macroinvertebrate and fish conditions and positive direct and indirect effects of altitude on NO₃‐N, riffle quality and macroinvertebrate and fish conditions. The 2002 Land Use model showed contemporary development and agriculture had positive total effects on NO₃‐N (both through direct pathways); contemporary development had negative effects on macroinvertebrate condition. The Land Use Change model showed that contemporary developed land that was forested in 1952 had no effects on NO₃‐N; current developed land that was developed or agricultural in 1952 showed positive effects on NO₃‐N. Forests that were agricultural in 1952 had negative effects on NO₃‐N, suggesting reduced NO₃‐N export with reforestation. The Land Use Change model also showed negative total effects of all types of contemporary developed land (developed, agricultural or forested in 1952) on benthic condition. Developed land that was forested in 1952 had negative effects on fish condition. Forest sites that were agricultural in 1952 had negative effects on fish and macroinvertebrate conditions, suggesting a long‐term imprint of abandoned agriculture in stream communities. 5. Our analyses (i) identified multiple indirect effects of contemporary land use on streams, (ii) showed that current land uses with different land use histories can exhibit different effects on streams and (iii) demonstrated an imprint of land use lasting >50 years. Knowledge of these indirect and long‐term effects of land use will help to conserve and restore streams.     

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.     

Land suitability for energy crops under scenarios of climate change and land‐use

Bioenergy is expected to play a critical role in climate change mitigation. Most integrated assessment models assume an expansion of agricultural land for cultivation of energy crops. This study examines the suitability of land for growing a range of energy crops on areas that are not required for food production, accounting for climate change impacts and conservation requirements. A global fuzzy logic model is employed to ascertain the suitable cropping areas for a number of sugar, starch and oil crops, energy grasses and short rotation tree species that could be grown specifically for energy. Two climate change scenarios are modelled (RCP2.6 and RCP8.5), along with two scenarios representing the land which cannot be used for energy crops due to forest and biodiversity conservation, food agriculture and urban areas. Results indicate that 40% of the global area currently suitable for energy crops overlaps with food land and 31% overlaps with forested or protected areas, highlighting hotspots of potential land competition risks. Approximately 18.8 million km² is suitable for energy crops, to some degree, and does not overlap with protected, forested, urban or food agricultural land. Under the climate change scenario RCP8.5, this increases to 19.6 million km² by the end of the century. Broadly, climate change is projected to decrease suitable areas in southern regions and increase them in northern regions, most notably for grass crops in Russia and China, indicating that potential production areas will shift northwards which could potentially affect domestic use and trade of biomass significantly. The majority of the land which becomes suitable is in current grasslands and is just marginally or moderately suitable. This study therefore highlights the vital importance of further studies examining the carbon and ecosystem balance of this potential land‐use change, energy crop yields in sub‐optimal soil and climatic conditions and potential impacts on livelihoods.     

Biodiversity scenarios neglect future land‐use changes

Efficient management of biodiversity requires a forward‐looking approach based on scenarios that explore biodiversity changes under future environmental conditions. A number of ecological models have been proposed over the last decades to develop these biodiversity scenarios. Novel modelling approaches with strong theoretical foundation now offer the possibility to integrate key ecological and evolutionary processes that shape species distribution and community structure. Although biodiversity is affected by multiple threats, most studies addressing the effects of future environmental changes on biodiversity focus on a single threat only. We examined the studies published during the last 25 years that developed scenarios to predict future biodiversity changes based on climate, land‐use and land‐cover change projections. We found that biodiversity scenarios mostly focus on the future impacts of climate change and largely neglect changes in land use and land cover. The emphasis on climate change impacts has increased over time and has now reached a maximum. Yet, the direct destruction and degradation of habitats through land‐use and land‐cover changes are among the most significant and immediate threats to biodiversity. We argue that the current state of integration between ecological and land system sciences is leading to biased estimation of actual risks and therefore constrains the implementation of forward‐looking policy responses to biodiversity decline. We suggest research directions at the crossroads between ecological and environmental sciences to face the challenge of developing interoperable and plausible projections of future environmental changes and to anticipate the full range of their potential impacts on biodiversity. An intergovernmental platform is needed to stimulate such collaborative research efforts and to emphasize the societal and political relevance of taking up this challenge.     

Recent land‐use changes affect stream ecosystem processes in a subtropical island in Brazil

Land‐use changes such as conversion of natural forest to rural and urban areas have been considered as main drivers of ecosystem functions decline, and a large variety of indicators has been used to investigate these effects. Here, we used a replicated litter‐bag experiment to investigate the effects of land‐use changes on the leaf‐litter breakdown process and leaf‐associated invertebrates along the forest–pasture–urban gradient located in a subtropical island (Florianópolis, SC, Brazil). We identified the invertebrates and measured the litter breakdown rates using the litter bags approach. Litter bags containing 3 g of dry leaf of Alchornea triplinervia were deployed on forest rural and urban streams. Principal component analysis, based on physico‐chemical variables which, confirmed a gradient of degradation from forest to urban streams with intermediate values in rural areas. In accordance, shredder richness and abundance were lower in rural and urban than in forest streams. The land‐use changes led also to the dominance of tolerant generalist taxa (Chironomidae and Oligochaeta) reducing the taxonomic and functional diversity in these sites. Leaf‐litter breakdown rates decreased from forest to rural and finally to urban areas and were associated with changes in pH, water velocity, dissolved oxygen and abundance of leaf‐shredding invertebrates, although global decomposition rates did not differ between rural and urban streams. Overall, this study showed that land‐use changes, namely to rural and urban areas, have a strong impact on tropical streams ecosystems, in both processes and communities composition and structure. Despite of being apparently a smaller transformation of landscape, rural land use is comparable to urbanisation in terms of impact in stream functioning. It is thus critical to carefully plan urban development and maintain forest areas in the island of Florianópolis in order to preserve its natural biodiversity and aquatic ecosystems functioning.     

Conventional land‐use intensification reduces species richness and increases production: A global meta‐analysis

Most current research on land‐use intensification addresses its potential to either threaten biodiversity or to boost agricultural production. However, little is known about the simultaneous effects of intensification on biodiversity and yield. To determine the responses of species richness and yield to conventional intensification, we conducted a global meta‐analysis synthesizing 115 studies which collected data for both variables at the same locations. We extracted 449 cases that cover a variety of areas used for agricultural (crops, fodder) and silvicultural (wood) production. We found that, across all production systems and species groups, conventional intensification is successful in increasing yield (grand mean + 20.3%), but it also results in a loss of species richness (?8.9%). However, analysis of sub‐groups revealed inconsistent results. For example, small intensification steps within low intensity systems did not affect yield or species richness. Within high‐intensity systems species losses were non‐significant but yield gains were substantial (+15.2%). Conventional intensification within medium intensity systems revealed the highest yield increase (+84.9%) and showed the largest loss in species richness (?22.9%). Production systems differed in their magnitude of richness response, with insignificant changes in silvicultural systems and substantial losses in crop systems (?21.2%). In addition, this meta‐analysis identifies a lack of studies that collect robust biodiversity (i.e. beyond species richness) and yield data at the same sites and that provide quantitative information on land‐use intensity. Our findings suggest that, in many cases, conventional land‐use intensification drives a trade‐off between species richness and production. However, species richness losses were often not significantly different from zero, suggesting even conventional intensification can result in yield increases without coming at the expense of biodiversity loss. These results should guide future research to close existing research gaps and to understand the circumstances required to achieve such win‐win or win‐no‐harm situations in conventional agriculture.     

Projecting impacts of global climate and land‐use scenarios on plant biodiversity using compositional‐turnover modelling

Nations have committed to ambitious conservation targets in response to accelerating rates of global biodiversity loss. Anticipating future impacts is essential to inform policy decisions for achieving these targets, but predictions need to be of sufficiently high spatial resolution to forecast the local effects of global change. As part of the intercomparison of biodiversity and ecosystem services models of the Intergovernmental Science‐Policy Platform on Biodiversity and Ecosystem Services, we present a fine‐resolution assessment of trends in the persistence of global plant biodiversity. We coupled generalized dissimilarity models, fitted to >52 million records of >254 thousand plant species, with the species–area relationship, to estimate the effect of land‐use and climate change on global biodiversity persistence. We estimated that the number of plant species committed to extinction over the long term has increased by 60% globally between 1900 and 2015 (from ~10,000 to ~16,000). This number is projected to decrease slightly by 2050 under the most optimistic scenario of land‐use change and to substantially increase (to ~18,000) under the most pessimistic scenario. This means that, in the absence of climate change, scenarios of sustainable socio‐economic development can potentially bring extinction risk back to pre‐2000 levels. Alarmingly, under all scenarios, the additional impact from climate change might largely surpass that of land‐use change. In this case, the estimated number of species committed to extinction increases by 3.7–4.5 times compared to land‐use‐only projections. African regions (especially central and southern) are expected to suffer some of the highest impacts into the future, while biodiversity decline in Southeast Asia (which has previously been among the highest globally) is projected to slow down. Our results suggest that environmentally sustainable land‐use planning alone might not be sufficient to prevent potentially dramatic biodiversity loss, unless a stabilization of climate to pre‐industrial times is observed.     

Largely underestimated carbon emission from land use and land cover change in the conterminous United States

Carbon (C) emission and uptake due to land use and land cover change (LULCC) are the most uncertain term in the global carbon budget primarily due to limited LULCC data and inadequate model capability (e.g., underrepresented agricultural managements). We take the commonly used FAOSTAT‐based global Land Use Harmonization data (LUH2) and a new high‐resolution multisource harmonized national LULCC database (YLmap) to drive a land ecosystem model (DLEM) in the conterminous United States. We found that recent cropland abandonment and forest recovery may have been overestimated in the LUH2 data derived from national statistics, causing previously reported C emissions from land use have been underestimated due to the definition of cropland and aggregated LULCC signals at coarse resolution. This overestimation leads to a strong C sink (30.3 ± 2.5 Tg C/year) in model simulations driven by LUH2 in the United States during the 1980–2016 period, while we find a moderate C source (13.6 ± 3.5 Tg C/year) when using YLmap. This divergence implies that previous C budget analyses based on the global LUH2 dataset have underestimated C emission in the United States owing to the delineation of suitable cropland and aggregated land conversion signals at coarse resolution which YLmap overcomes. Thus, to obtain more accurate quantification of LULCC‐induced C emission and better serve global C budget accounting, it is urgently needed to develop fine‐scale country‐specific LULCC data to characterize the details of land conversion.     

Synergistic effects of climate and land‐use change influence broad‐scale avian population declines

Climate and land‐use changes are expected to be the primary drivers of future global biodiversity loss. Although theory suggests that these factors impact species synergistically, past studies have either focused on only one in isolation or have substituted space for time, which often results in confounding between drivers. Tests of synergistic effects require congruent time series on animal populations, climate change and land‐use change replicated across landscapes that span the gradient of correlations between the drivers of change. Using a unique time series of high‐resolution climate (measured as temperature and precipitation) and land‐use change (measured as forest change) data, we show that these drivers of global change act synergistically to influence forest bird population declines over 29 years in the Pacific Northwest of the United States. Nearly half of the species examined had declined over this time. Populations declined most in response to loss of early seral and mature forest, with responses to loss of early seral forest amplified in landscapes that had warmed over time. In addition, birds declined more in response to loss of mature forest in areas that had dried over time. Climate change did not appear to impact populations in landscapes with limited habitat loss, except when those landscapes were initially warmer than the average landscape. Our results provide some of the first empirical evidence of synergistic effects of climate and land‐use change on animal population dynamics, suggesting accelerated loss of biodiversity in areas under pressure from multiple global change drivers. Furthermore, our findings suggest strong spatial variability in the impacts of climate change and highlight the need for future studies to evaluate multiple drivers simultaneously to avoid potential misattribution of effects.     

Contrasting effects of land‐use changes on herbivory and pollination networks

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Biodiversity responses to land‐use and restoration in a global biodiversity hotspot: Ant communities in Brazilian Cerrado

Given that land‐use change is the main cause of global biodiversity decline, there is widespread interest in adopting land‐use practices that maintain high levels of biodiversity, and in restoring degraded land that previously had high biodiversity value. In this study, we use ant taxonomic and functional diversity to examine the effects of different land uses (agriculture, pastoralism, silviculture and conservation) and restoration practices on Cerrado (Brazilian savanna) biodiversity. We also examine the extent to which ant diversity and composition can be explained by vegetation attributes that apply across the full land management spectrum. We surveyed vegetation attributes and ant communities in five replicate plots of each of 13 land‐use and restoration treatments, including two types of native vegetation as reference sites: cerrado sensu stricto and cerradão. Several land‐use and restoration treatments had comparable plot richness to that of the native reference habitats. Ant species and functional composition varied systematically among land‐use treatments following a gradient from open habitats such as agricultural fields to forested sites. Tree basal area and grass cover were the strongest predictors of ant species richness. Losses in ant diversity were higher in land‐use systems that transform vegetation structure. Among productive systems, therefore, uncleared pastures and old pine plantations had similar species composition to that occurring in cerrado sensu stricto. Restoration techniques currently applied to sites that were previously Cerrado have focused on returning tree cover, and have failed to restore ant communities typical of savanna. To improve restoration outcomes for Cerrado biodiversity, greater attention needs to be paid to the re‐establishment and maintenance of the grass layer, which requires frequent fire. At the broader scale, conservation planning in agricultural landscapes, should recognize the value of land‐use mosaics and the risks of homogenization.     

Anticipated climate and land‐cover changes reveal refuge areas for Borneo's orang‐utans

Habitat loss and climate change pose a double jeopardy for many threatened taxa, making the identification of optimal habitat for the future a conservation priority. Using a case study of the endangered Bornean orang‐utan, we identify environmental refuges by integrating bioclimatic models with projected deforestation and oil‐palm agriculture suitability from the 1950s to 2080s. We coupled a maximum entropy algorithm with information on habitat needs to predict suitable habitat for the present day and 1950s. We then projected to the 2020s, 2050s and 2080s in models incorporating only land‐cover change, climate change or both processes combined. For future climate, we incorporated projections from four model and emission scenario combinations. For future land cover, we developed spatial deforestation predictions from 10 years of satellite data. Refuges were delineated as suitable forested habitats identified by all models that were also unsuitable for oil palm – a major threat to tropical biodiversity. Our analyses indicate that in 2010 up to 260 000 km² of Borneo was suitable habitat within the core orang‐utan range; an 18–24% reduction since the 1950s. Land‐cover models predicted further decline of 15–30% by the 2080s. Although habitat extent under future climate conditions varied among projections, there was majority consensus, particularly in north‐eastern and western regions. Across projections habitat loss due to climate change alone averaged 63% by 2080, but 74% when also considering land‐cover change. Refuge areas amounted to 2000–42 000 km² depending on thresholds used, with 900–17 000 km² outside the current species range. We demonstrate that efforts to halt deforestation could mediate some orang‐utan habitat loss, but further decline of the most suitable areas is to be expected given projected changes to climate. Protected refuge areas could therefore become increasingly important for ongoing translocation efforts. We present an approach to help identify such areas for highly threatened species given environmental changes expected this century.     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.     

Soil carbon dynamics following land‐use change varied with temperature and precipitation gradients: evidence from stable isotopes

Knowledge of soil organic matter (SOM) dynamics following deforestation or reforestation is essential for evaluating carbon (C) budgets and cycle at regional or global scales. Worldwide land‐use changes involving conversion of vegetation with different photosynthetic pathways (e.g. C₃ and C₄) offer a unique opportunity to quantify SOM decomposition rate and its response to climatic conditions using stable isotope techniques. We synthesized the results from 131 sites (including 87 deforestation observations and 44 reforestation observations) which were compiled from 36 published papers in the literatures as well as our observations in China's Qinling Mountains. Based on the ¹³C natural abundance analysis, we evaluated the dynamics of new and old C in top soil (0–20 cm) following land‐use change and analyzed the relationships between soil organic C (SOC) decomposition rates and climatic factors. We found that SOC decomposition rates increased significantly with mean annual temperature and precipitation in the reforestation sites, and they were not related to any climatic factor in deforestation sites. The mean annual temperature explained 56% of variation in SOC decomposition rates by exponential model (y = 0.0014e^0.1395x) in the reforestation sites. The proportion of new soil C increased following deforestation and reforestation, whereas the old soil C showed an opposite trend. The proportion of new soil C exceeded the proportion of old soil C after 45.4 years' reforestation and 43.4 years' deforestation, respectively. The rates of new soil C accumulation increased significantly with mean annual precipitation and temperature in the reforestation sites, yet only significantly increased with mean annual precipitation in the deforestation sites. Overall, our study provides evidence that SOC decomposition rates vary with temperature and precipitation, and thereby implies that global warming may accelerate SOM decomposition.     

Mangrove blue carbon stocks and dynamics are controlled by hydrogeomorphic settings and land‐use change

Globally, carbon‐rich mangrove forests are deforested and degraded due to land‐use and land‐cover change (LULCC). The impact of mangrove deforestation on carbon emissions has been reported on a global scale; however, uncertainty remains at subnational scales due to geographical variability and field data limitations. We present an assessment of blue carbon storage at five mangrove sites across West Papua Province, Indonesia, a region that supports 10% of the world's mangrove area. The sites are representative of contrasting hydrogeomorphic settings and also capture change over a 25‐years LULCC chronosequence. Field‐based assessments were conducted across 255 plots covering undisturbed and LULCC‐affected mangroves (0‐, 5‐, 10‐, 15‐ and 25‐year‐old post‐harvest or regenerating forests as well as 15‐year‐old aquaculture ponds). Undisturbed mangroves stored total ecosystem carbon stocks of 182–2,730 (mean ± SD: 1,087 ± 584) Mg C/ha, with the large variation driven by hydrogeomorphic settings. The highest carbon stocks were found in estuarine interior (EI) mangroves, followed by open coast interior, open coast fringe and EI forests. Forest harvesting did not significantly affect soil carbon stocks, despite an elevated dead wood density relative to undisturbed forests, but it did remove nearly all live biomass. Aquaculture conversion removed 60% of soil carbon stock and 85% of live biomass carbon stock, relative to reference sites. By contrast, mangroves left to regenerate for more than 25 years reached the same level of biomass carbon compared to undisturbed forests, with annual biomass accumulation rates of 3.6 ± 1.1 Mg C ha^?1 year^?1. This study shows that hydrogeomorphic setting controls natural dynamics of mangrove blue carbon stocks, while long‐term land‐use changes affect carbon loss and gain to a substantial degree. Therefore, current land‐based climate policies must incorporate landscape and land‐use characteristics, and their related carbon management consequences, for more effective emissions reduction targets and restoration outcomes.     

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.     

A regional assessment of land‐based carbon mitigation potentials: Bioenergy,BECCS, reforestation,and forest management

Land‐based solutions are indispensable features of most climate mitigation scenarios. Here we conduct a novel cross‐sectoral assessment of regional carbon mitigation potential by running an ecosystem model with an explicit representation of forest structure and climate impacts for Bavaria, Germany, as a case study. We drive the model with four high‐resolution climate projections (EURO‐CORDEX) for the representative concentration pathway RCP4.5 and present‐day land‐cover from three satellite‐derived datasets (CORINE, ESA‐CCI, MODIS) and identify total mitigation potential by not only accounting for carbon storage but also material and energy substitution effects. The model represents the current state in Bavaria adequately, with a simulated forest biomass 12.9 ± 0.4% lower than data from national forest inventories. Future land‐use changes according to two ambitious land‐use harmonization scenarios (SSP1xRCP2.6, SSP4xRCP3.4) achieve a mitigation of 206 and 247 Mt C (2015–2100 period) via reforestation and the cultivation and burning of dedicated bioenergy crops, partly combined with carbon capture and storage. Sensitivity simulations suggest that converting croplands or pastures to bioenergy plantations could deliver a carbon mitigation of 40.9 and 37.7 kg C/m², respectively, by the year 2100 if used to replace carbon‐intensive energy systems and combined with CCS. However, under less optimistic assumptions (including no CCS), only 15.3 and 12.2 kg C/m² are mitigated and reforestation might be the better option (20.0 and 16.8 kg C/m²). Mitigation potential in existing forests is limited (converting coniferous into mixed forests, nitrogen fertilization) or even negative (suspending wood harvest) due to decreased carbon storage in product pools and associated substitution effects. Our simulations provide guidelines to policy makers, farmers, foresters, and private forest owners for sustainable and climate‐benefitting ecosystem management in temperate regions. They also emphasize the importance of the CCS technology which is regarded critically by many people, making its implementation in the short or medium term currently doubtable.     

Quantifying global greenhouse gas emissions from land‐use change for crop production

Many assessments of product carbon footprint (PCF) for agricultural products omit emissions arising from land‐use change (LUC). In this study, we developed a framework based on IPCC national greenhouse gas inventory methodologies to assess the impacts of LUC from crop production using oil palm, soybean and oilseed rape as examples. Using ecological zone, climate and soil types from the top 20 producing countries, calculated emissions for transitions from natural vegetation to cropland on mineral soils under typical management ranged from ?4.5 to 29.4 t CO₂‐eq ha^?1 yr^?1 over 20 years for oil palm and 1.2–47.5 t CO₂‐eq ha^?1 yr^?1 over 20 years for soybeans. Oilseed rape showed similar results to soybeans, but with lower maximum values because it is mainly grown in areas with lower C stocks. GHG emissions from other land‐use transitions were between 62% and 95% lower than those from natural vegetation for the arable crops, while conversions to oil palm were a sink for C. LUC emissions were considered on a national basis and also expressed per‐tonne‐of‐oil‐produced. Weighted global averages indicate that, depending on the land‐use transition, oil crop production on newly converted land contributes between ?3.1 and 7.0 t CO₂‐eq t oil production^?1 yr^?1 for palm oil, 11.9–50.6 t CO₂‐eq t oil production^?1 yr^?1 for soybean oil, and 7.7–31.4 t CO₂‐eq t oil production^?1 yr^?1 for rapeseed oil. Assumptions made about crop and LUC distribution within countries contributed up to 66% error around the global averages for natural vegetation conversions. Uncertainty around biomass and soil C stocks were also examined. Finer resolution data and information (particularly on land management and yield) could improve reliability of the estimates but the framework can be used in all global regions and represents an important step forward for including LUC emissions in PCFs.     

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.