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.     

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.     

Mitigation of unwanted direct and indirect land‐use change – an integrated approach illustrated for palm oil,pulpwood, rubber and rice production in North and East Kalimantan,Indonesia

The widespread production of cash crops can result in the decline of forests, peatlands, rice fields and local community land. Such unwanted land‐use and land‐cover (LULC) change can lead to decreased carbon stocks, diminished biodiversity, displaced communities and reduced local food production. In this study, we analysed to what extent four main commodities, namely, palm oil, pulpwood, rice and rubber, can be produced in North and East Kalimantan in Indonesia without such unwanted LULC change. We investigated the technical potential of four measures to mitigate unwanted LULC change between 2008 and 2020 under low, medium and high scenarios, referring to the intensities of the mitigation measures compared with those implemented in 2008. These measures are related to land sparing through (i) the improvements of yields, (ii) chain efficiencies, (iii) chain integration and (iv) the steering of any expansion of these commodities to suitable and available underutilised (potentially degraded) lands. Our analyses resulted in a land‐sparing potential of 0.4–1.2 Mha (i.e. 24–62% of the total land demand of the commodities) between 2008 and 2020, depending on the land‐use projection of the four commodities and the scenario for implementing the mitigation measures. Additional expansion on underutilised land is the most important mitigation measure (45–62% of the total potential), followed by yield improvements as the second most important mitigation measure (32–46% of the total potential). Our study shows that reconciling the production of palm oil, pulpwood, rice and rubber with the maintenance of existing agricultural lands, forests and peatlands is technically possible only (i) under a scenario of limited agricultural expansion, (ii) if responsible land zoning is applied and enforced and (iii) if the yields and chain efficiencies are strongly improved.     

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.     

Global environmental change effects on ecosystems: the importance of land‐use legacies

One of the major challenges in ecology is to predict how multiple global environmental changes will affect future ecosystem patterns (e.g. plant community composition) and processes (e.g. nutrient cycling). Here, we highlight arguments for the necessary inclusion of land‐use legacies in this endeavour. Alterations in resources and conditions engendered by previous land use, together with influences on plant community processes such as dispersal, selection, drift and speciation, have steered communities and ecosystem functions onto trajectories of change. These trajectories may be modulated by contemporary environmental changes such as climate warming and nitrogen deposition. We performed a literature review which suggests that these potential interactions have rarely been investigated. This crucial oversight is potentially due to an assumption that knowledge of the contemporary state allows accurate projection into the future. Lessons from other complex dynamic systems, and the recent recognition of the importance of previous conditions in explaining contemporary and future ecosystem properties, demand the testing of this assumption. Vegetation resurvey databases across gradients of land use and environmental change, complemented by rigorous experiments, offer a means to test for interactions between land‐use legacies and multiple environmental changes. Implementing these tests in the context of a trait‐based framework will allow biologists to synthesize compositional and functional ecosystem responses. This will further our understanding of the importance of land‐use legacies in determining future ecosystem properties, and soundly inform conservation and restoration management actions.     

The influence of time,soil characteristics,and land‐use history on soil phosphorus legacies: a global meta‐analysis

Agriculturally driven changes in soil phosphorus (P) are known to have persistent effects on local ecosystem structure and function, but regional patterns of soil P recovery following cessation of agriculture are less well understood. We synthesized data from 94 published studies to assess evidence of these land‐use legacies throughout the world by comparing soil labile and total P content in abandoned agricultural areas to that of reference ecosystems or sites remaining in agriculture. Our meta‐analysis shows that soil P content was typically elevated after abandonment compared to reference levels, but reduced compared to soils that remained under agriculture. There were more pronounced differences in the legacies of past agriculture on soil P across regions than between the types of land use practiced prior to abandonment (cropland, pasture, or forage grassland). However, consistent patterns of soil P enrichment or depletion according to soil order and types of post‐agricultural vegetation suggest that these factors may mediate agricultural legacies on soil P. We also used mixed effects models to examine the role of multiple variables on soil P recovery following agriculture. Time since cessation of agriculture was highly influential on soil P legacies, with clear reductions in the degree of labile and total P enrichment relative to reference ecosystems over time. Soil characteristics (clay content and pH) were strongly related to changes in labile P compared to reference sites, but these were relatively unimportant for total P. The duration of past agricultural use and climate were weakly related to changes in total P only. Our finding of reductions in the degree of soil P alteration over time relative to reference conditions reveals the potential to mitigate these land‐use legacies in some soils. Better ability to predict dynamics of soil nutrient recovery after termination of agricultural use is essential to ecosystem management following land‐use change.     

Effect of agricultural land‐use change on the structure of a temperate forest ant–plant interaction network

Studies on the responses of ant–plant interactions to land‐use change have mainly focused on tropical habitats, usually without considering the impacts on the structure of interaction networks. Here we show that land‐use modifies the structure of the ant–plant interaction networks in a temperate habitat. Ant–plant interactions and plant diversity were recorded in an oak forest and agricultural land in central Mexico. We registered five ant species in the oak forest, and four ant species in the agricultural land. Plant diversity was higher in the agricultural land than in the oak forest. In the ant–plant networks of both sites, our results showed a higher dependence of ants on the plants on which they feed than vice versa, and the ants Formica spp. and the plants Barkleyanthus salicifolius were the species with the most strength and greatest influence in the network structure. The ant–plant network in the oak forest showed a nested structure. However, the network at the agricultural land site showed non‐nestedness; the identity of both ants and plants with the highest values of specialization was different and the number of ant species in the network was decreased, but the number of plant species with which they interacted significantly increased. Both ant–plant networks were equally tolerant to simulated extinction of individual species. We conclude that temperate forest ant–plant networks can be inherently fragile and susceptible to the effects of agricultural land‐use change, not on the number of interacting species but on their identity.     

Land cover change or land‐use intensification: simulating land system change with a global‐scale land change model

Land‐use change is both a cause and consequence of many biophysical and socioeconomic changes. The CLUMondo model provides an innovative approach for global land‐use change modeling to support integrated assessments. Demands for goods and services are, in the model, supplied by a variety of land systems that are characterized by their land cover mosaic, the agricultural management intensity, and livestock. Land system changes are simulated by the model, driven by regional demand for goods and influenced by local factors that either constrain or promote land system conversion. A characteristic of the new model is the endogenous simulation of intensification of agricultural management versus expansion of arable land, and urban versus rural settlements expansion based on land availability in the neighborhood of the location. Model results for the OECD Environmental Outlook scenario show that allocation of increased agricultural production by either management intensification or area expansion varies both among and within world regions, providing useful insight into the land sparing versus land sharing debate. The land system approach allows the inclusion of different types of demand for goods and services from the land system as a driving factor of land system change. Simulation results are compared to observed changes over the 1970–2000 period and projections of other global and regional land change models.     

Land‐use conversion and changing soil carbon stocks in China's ‘Grain‐for‐Green’ Program: a synthesis

The establishment of either forest or grassland on degraded cropland has been proposed as an effective method for climate change mitigation because these land use types can increase soil carbon (C) stocks. This paper synthesized 135 recent publications (844 observations at 181 sites) focused on the conversion from cropland to grassland, shrubland or forest in China, better known as the ‘Grain‐for‐Green’ Program to determine which factors were driving changes to soil organic carbon (SOC). The results strongly indicate a positive impact of cropland conversion on soil C stocks. The temporal pattern for soil C stock changes in the 0–100 cm soil layer showed an initial decrease in soil C during the early stage (<5 years), and then an increase to net C gains (>5 years) coincident with vegetation restoration. The rates of soil C change were higher in the surface profile (0–20 cm) than in deeper soil (20–100 cm). Cropland converted to forest (arbor) had the additional benefit of a slower but more persistent C sequestration capacity than shrubland or grassland. Tree species played a significant role in determining the rate of change in soil C stocks (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.     

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.     

Long‐term terrestrial carbon dynamics in the Midwestern United States during 1850–2015: Roles of land use and cover change and agricultural management

To meet the increasing food and biofuel demand, the Midwestern United States has become one of the most intensively human‐disturbed hotspots, characterized by widespread cropland expansion and various management practices. However, the role of human activities in the carbon (C) cycling across managed landscape remains far from certain. In this study, based on state‐ and national census, field experiments, and model simulation, we comprehensively examined long‐term carbon storage change in response to land use and cover change (LUCC) and agricultural management in the Midwest from 1850 to 2015. We also quantified estimation uncertainties related to key parameter values. Model estimation showed LUCC led to a reduction of 1.35 Pg (with a range of 1.3–1.4 Pg) in vegetation C pool of the Midwest, yet agricultural management barely affected vegetation C change. In comparison, LUCC reduced SOC by 4.5 Pg (3.1 to 6.2 Pg), while agricultural management practices increased SOC stock by 0.9 Pg. Moreover, we found 45% of the study area was characterized by continuously decreasing SOC caused by LUCC, and SOC in 13% and 31% of the area was fully and partially recovered, respectively, since 1850. Agricultural management was estimated to increase the area of full recovery and partial recovery by 8.5% and 1.1%. Our results imply that LUCC plays an essential role in regional C balance, and more importantly, sustainable land management can be beneficial for strengthening C sequestration of the agroecosystems in the Midwestern US, which may serve as an important contributor to C sinks in the US.     

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 HYDE 3.1 spatially explicit database of human‐induced global land‐use change over the past 12,000 years

Aim This paper presents a tool for long‐term global change studies; it is an update of the History Database of the Global Environment (HYDE) with estimates of some of the underlying demographic and agricultural driving factors. Methods Historical population, cropland and pasture statistics are combined with satellite information and specific allocation algorithms (which change over time) to create spatially explicit maps, which are fully consistent on a 5′ longitude/latitude grid resolution, and cover the period 10,000 bc to ad 2000. Results Cropland occupied roughly less than 1% of the global ice‐free land area for a long time until ad 1000, similar to the area used for pasture. In the centuries that followed, the share of global cropland increased to 2% in ad 1700 (c. 3 million km²) and 11% in ad 2000 (15 million km²), while the share of pasture area grew from 2% in ad 1700 to 24% in ad 2000 (34 million km²) These profound land‐use changes have had, and will continue to have, quite considerable consequences for global biogeochemical cycles, and subsequently global climate change. Main conclusions Some researchers suggest that humans have shifted from living in the Holocene (emergence of agriculture) into the Anthropocene (humans capable of changing the Earth's atmosphere) since the start of the Industrial Revolution. But in the light of the sheer size and magnitude of some historical land‐use changes (e.g. as result of the depopulation of Europe due to the Black Death in the 14th century and the aftermath of the colonization of the Americas in the 16th century) we believe that this point might have occurred earlier in time. While there are still many uncertainties and gaps in our knowledge about the importance of land use (change) in the global biogeochemical cycle, we hope that this database can help global (climate) change modellers to close parts of this gap.     

Species richness and evenness respond to diverging land‐use patterns – a cross‐border study of dry tropical woodlands in southern Africa

Cross‐border studies offer unique situations to study the impact of different land‐use regimes on ecosystems. Along the Angolan and Namibian border formed by the Okavango River, the environmental conditions and traditional land‐use practises are the same on either side of the river. However, decades of civil war in Angola led to a stagnant development while political stability in Namibia fostered a recent socio‐economic transformation. We investigated the impact of spatially diffuse land use on plant diversity of the dry tropical woodlands covering the vast, sandy hinterlands of the river. As accessibility is the major factor governing land use, we used distance to road as a proxy for land‐use intensity. Based on 58 vegetation plots sized 20 m × 50 m, we showed that species richness increased with distance to road in Angola while in Namibia it remained constant on a lower level. Evenness showed an inverse pattern to species richness and Shannon diversity index showed no response. Analysing diversity patterns according to life forms revealed that these patterns are primarily driven by woody species. The study showed that spatially diffuse land use has a measurable effect on plant diversity and illustrates that roads act as vectors of change.     

Predicting the potential distribution of a riparian invasive plant: the effects of changing climate,flood regimes and land‐use patterns

Climate change is likely to affect plants in multiple ways, but predicting the consequences for habitat suitability requires a process‐based understanding of the interactions. This is at odds with existing approaches that are mostly phenomenological and largely restricted to predicting the effects of changing temperature and rainfall on species distributions at a coarse spatial scale. We examine the multiple effects of climate change, including predicting the effects of altered flood regimes and land‐use change, on the potential distribution of the invasive riparian species lippia (Phyla canescens) across a 26 000 km² catchment in eastern Australia. We determined habitat suitability for lippia by combining process‐understanding of experts and an eco‐physiological bioclimatic model within a Bayesian belief network. The bioclimatic model predicted substantial changes in habitat suitability by 2070 under both a wetter (Echam Mark 3) and drier (Hadley Centre Mark 2) climate change scenario, but only the more likely drier scenario reduced suitability in our test region. The area suitable for lippia was predicted to increase at least threefold with increased flooding under a wet climate scenario, although this would be partially negated by land‐use change to cultivation. The region would become unsuitable to lippia with reduced flooding under a drier scenario irrespective of land‐use changes, although existing populations would persist if grazing persisted. Independent field validation verified model structure and parameterization, and therefore the opinion of experts, but identified site‐scale deficiencies in the available environmental data layers. Model predictions suggest that adaptation options for managing lippia will be greatly reduced under a drying scenario, but identify potential restoration opportunities under either scenario. This work highlights the value of predictive models that incorporate process‐understanding at sufficiently fine spatial resolution to capture the important processes underpinning habitat suitability.     

Temporal dynamics of soil organic carbon after land‐use change in the temperate zone – carbon response functions as a model approach

Land‐use change (LUC) is a major driving factor for the balance of soil organic carbon (SOC) stocks and the global carbon cycle. The temporal dynamic of SOC after LUC is especially important in temperate systems with a long reaction time. On the basis of 95 compiled studies covering 322 sites in the temperate zone, carbon response functions (CRFs) were derived to model the temporal dynamic of SOC after five different LUC types (mean soil depth of 30±6 cm). Grassland establishment caused a long lasting carbon sink with a relative stock change of 128±23% and afforestation on former cropland a sink of 116±54%, 100 years after LUC (mean±95% confidence interval). No new equilibrium was reached within 120 years. In contrast, there was no SOC sink following afforestation of grasslands and 75% of all observations showed SOC losses, even after 100 years. Only in the forest floor, there was carbon accumulation of 0.38±0.04 Mg ha^?1 yr^?1 in afforestations adding up to 38±4 Mg ha^?1 labile carbon after 100 years. Carbon loss after deforestation (?32±20%) and grassland conversion to cropland (?36±5%), was rapid with a new SOC equilibrium being reached after 23 and 17 years, respectively. The change rate of SOC increased with temperature and precipitation but decreased with soil depth and clay content. Subsoil SOC changes followed the trend of the topsoil SOC changes but were smaller (25±5% of the total SOC changes) and with a high uncertainty due to a limited number of datasets. As a simple and robust model approach, the developed CRFs provide an easily applicable tool to estimate SOC stock changes after LUC to improve greenhouse gas reporting in the framework of UNFCCC.     

Large‐scale impact of climate change vs. land‐use change on future biome shifts in Latin America

Climate change and land‐use change are two major drivers of biome shifts causing habitat and biodiversity loss. What is missing is a continental‐scale future projection of the estimated relative impacts of both drivers on biome shifts over the course of this century. Here, we provide such a projection for the biodiverse region of Latin America under four socio‐economic development scenarios. We find that across all scenarios 5–6% of the total area will undergo biome shifts that can be attributed to climate change until 2099. The relative impact of climate change on biome shifts may overtake land‐use change even under an optimistic climate scenario, if land‐use expansion is halted by the mid‐century. We suggest that constraining land‐use change and preserving the remaining natural vegetation early during this century creates opportunities to mitigate climate‐change impacts during the second half of this century. Our results may guide the evaluation of socio‐economic scenarios in terms of their potential for biome conservation under global change.     

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.     

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.