Projections Of Land Use Research Articles

Modeling future projections of land use and land cover in the Kakataibo territory

Abstract. The Amazon region is undergoing a dynamic and extensive transformation from forested areas to human-altered landscapes, significantly impacting forests and indigenous territories. This research aims to create future land use and land cover (LULC) scenarios by examining past trends (2014–2022) and predicting future patterns for 2030, focusing on the Kakataibo territory in central Peru. Using the Dinamica EGO modelling platform, we projected LULC changes based on historical data and various predictive factors. Our findings reveal notable forest loss between 2014 and 2022, with this trend likely continuing through 2030. Within indigenous territories, deforestation was less severe, with a reduction of 30,247.4 hectares compared to the more significant loss in non-indigenous areas. This underscores the vital role these territories play in mitigating forest loss. However, the rapid expansion of agriculture and infrastructure within these regions signals an urgent need for stronger legal protections to halt further deforestation. This study highlights the critical importance of indigenous territories in forest conservation and offers valuable insights for future land management and conservation strategies in the Amazon.

Long-term stability in protected-areas? A vision from American/New World amphibians

Protected areas (PA) have proven to be one of the best ways to conserve biodiversity against environmental changes. Amphibians are considered the most threatened group, with habitat loss due to deforestation identified as their major threat. Here, we assessed for each PA of the American continent: 1) amphibian’s occurrence (Global Biodiversity Information Facility (GBIF) vs. International Union for Conservation of Nature (IUCN) data); 2) temperature velocity and estimated the climate residence time, and using the latest models of the land future use; 3) we estimated the changes of natural vs. modified cover in three future scenarios. Amphibian occurrence showed differences between databases, while GBIF data shows that 52 % of the amphibian species occurring in the continent are in PA, based on IUCN data, 85 % are protected. Results from climate change show a low pace of climate velocity during the last century that is maintained in the green scenario (SSP126). However, change in temperature increases in rate in the rest of the scenarios, with scenario SSP58 showing the highest velocity of temperature change. Future estimates of residence times in PA show that lower levels as emission scenarios tend to be higher. These results are worrisome since climate lag, specifically temperature increase over the PA will probably affect amphibian communities as shown in previous studies. Changes in climate patterns have a direct—mostly negative—impact on amphibians’ ability to disperse and reproduce. The results of land use change were unexpected, since the categories showed minimal changes. However, the data on urbanization changes do not seem to be reflecting the trends of other databases, which may be causing artifacts in the comparisons in the future models of land use. Further research will be necessary to evaluate the extent of similarities and differences in future projections of land use including urbanization and human population between different databases.

Urban land use simulation and carbon-related driving factors analysis based on RF-CA in Shanghai, China

As global climate change intensifies, climate protection is important for the sustainable development of human society. In the process of urbanization and industrialization, carbon dioxide emissions are an important factor contributing to global warming. Therefore, modelling projections of future urban land use under low-carbon scenarios are essential for sustainability policy development. Few studies have focused on the impact of carbon emissions on urban land use change in Shanghai, as current research has primarily concentrated on developing methods for urban land use modelling. This paper utilizes a cellular automata (CA) simulation model based on the Random Forest (RF) algorithm to select various spatial variables of carbon emissions as the driving factors that affect urban land use changes. These variables include traffic location factors, economic development factors, electricity consumption, and population density. In this study, remote sensing imagery of urban nighttime lighting is also used to construct a simulation model of land use types in Shanghai. The model is then used to analyze the contribution of carbon emission constraints to urban land use changes. Actual historical land use data from 2013 and 2019 are used for validation, and the prediction model is used to predict land use outcomes under different low-carbon scenarios in 2025. The model is validated by simulating multiple intra-city land use maps for 2019 (kappa = 0.88, OA=92.71 %). The method of out-of-bag error from the random forest is used to evaluate the significance of carbon emission constraints. Using the validated model, the constraints in the CA model are changed to predict the land use simulation results of Shanghai in 2025 under different low-carbon scenarios. In terms of significance, factors such as distance to power plants, distance to major roads, real GDP, and population density can all have a significant impact on changes in urban land use. By selecting the low-carbon scenario with the most appropriate thresholds for each driver, it is possible to obtain the land use simulation results of Shanghai in 2025 under the optimal low-carbon scenario, while ensuring the high accuracy of the RF-CA model and simultaneously reducing the impact of factors on the city’s overall carbon emissions. This paper provides a scientific base for urban planners and scholars to thoughtfully design urban land use while cutting down on carbon emissions. Furthermore, it can aid government agencies in establishing associated planning approaches.

Projections of Aedes and Culex mosquitoes across North and South America in response to climate change

IntroductionClimate and land use change may cause the geographical range of mosquitoes to expand, shift, or contract, ultimately changing what communities are at risk for contracting mosquito-borne diseases. Across North and South America, mosquitoes from the Aedes and Culex genera are vectors for numerous diseases, including chikungunya, dengue, various equine encephalitis viruses, Saint Louis encephalitis virus, West Nile virus, yellow fever virus, and Zika virus. The goal of our study was to project the geographical distributions of important mosquito vectors across North and South America in response to climate change, which is important to inform public health planning. MethodsWe used an ecological niche model and future projections of climate and land use to project the geographical ranges of two Aedes species (Ae. aegypti, Ae. albopictus) and seven Culex species (Cx. erraticus, Cx. nigripalpus, Cx. pipiens, Cx. quinquefasciatus, Cx. restuans, Cx. salinarius, Cx. tarsalis) over North and South America in response to both a high (Shared Socioeconomic Pathway [SSP] 5, Representative Concentration Pathway [RCP] 8.5) and moderate (SSP2 RCP4.5) climate warming scenario through years 2050 and 2090. ResultsFor SSP5 RCP8.5, six species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus, Cx. restuans) are projected to expand in geographical range, two species (Cx. pipiens, Cx. tarsalis) are projected to shift in geographical range, and one species (Cx. salinarius) is projected to nearly remain the same. Five species (Ae. aegypti, Ae. albopictus, Cx. erraticus, Cx. nigripalpus, Cx. quinquefasciatus) show the largest increase in high habitat suitability (>0.5 on a 0–1 scale) for SSP5 RCP8.5, three species (Cx. pipiens, Cx. restuans, Cx. tarsalis) show the largest increase for SSP2 RCP4.5, and one species (Cx. salinarius) shows a relatively small decrease in response to both scenarios. ConclusionsWe found that all nine species responded resiliently to climate change under both the high and moderate climate warming scenario, suggesting mosquito-borne disease is likely to be a continued threat in response to climate change. The projected geographical ranges can be used to inform disease risk analyses and mitigation strategies in response to climate change.

Ecological zoning and dynamic assessment of effectiveness in the Three Gorges Reservoir Area, China

Human activities render ecological conservation a formidable challenge. The rational zoning and dynamic evaluation of ecological regions are critical for the protection of regional biodiversity and the promotion of ecological sustainability. Here, the InVEST-HFI model was used to evaluate both the habitat quality (HQ) and the human footprint index (HFI) of the Three Gorges Reservoir Area (TGRA), a representative ecologically vulnerable area in southwest China. Superimposition analysis was employed to identify eco-regional zoning types and the PLUS model was applied to simulate and evaluate the benefits of ecological zoning. The results showed that the overall HQ of the TGRA area is satisfactory, with high-grade HQ areas covering 50.16 % of the entire reservoir area, mainly distributed in the Hubei section. The HFI displays a spatial distribution pattern, with higher values concentrated in the southwest and lower values in the northeast; there was also a concentration of high-value areas in Chongqing. Based on the HQ and HFI, the TGRA can be divided into three ecological protection zone types—a strict ecological protection zone, accounting for 57.18 % of the total area and distributed in the head and belly of the reservoir; a habitat restoration zone, accounting for 17.45 % of the total area and distributed in the tail of the reservoir; and a moderate development zone, which is scattered along the main stream of the Yangtze River in the middle of the reservoir. Simulation projections of land use in the TGRA for natural development and zoning protection scenarios until 2035 revealed that the ecosystem service value (ESV) of the latter scenario is 2.25 billion yuan higher than that of the former. Ecological zoning management can improve the ESV of the TGRA. We demonstrated the effectiveness of utilizing the HQ and HFI measures in ecological zoning, thus providing a valuable reference for assessing its benefits.

Spatial Rearrangement of Manufacturing Industrial Zones Based on MCDM in Mojokerto Regency. Case Study Northern Mojokerto Region

Mojokerto Regency is part of the national strategic area (Gerbangkertasusila) in East Java. Gerbangkertasusila serves as the driving force behind East Java’s economy, with the manufacturing industry becoming the prime mover as it contributes to 2022 GRDP by 56.68 percent. The spatial plan of Mojokerto Regency includes the development of an industrial estate in the northern part, specifically in Jetis and Dawarblandong Districts, covering a total area of 8.553 hectares. However, the government’s attempt to make industrial estates has only been realized by 2.65% since 2012. This research aims to assess the suitability of space allocation within the industrial estates in the northern region of Mojokerto. The research method uses spatial analysis approach, multi criteria decision making (MCDM). Spatial data were obtained through RBI and Bhumi ATR, also Mojokerto Regency’s RTRW as comparative data to assess the suitability of industrial locations. This study also considers other spatial aspects, such as projections of land use based on cellular automata, population, infrastructure, transportation, and physical conditions. Analysis result shows that the allocation of space requirements for industrial estate development is 1,081 hectares or 12.64 percent of the original plan. The area is much smaller than the planned area in the Mojokerto Regency’s RTRW. The study identifies four potential locations for Industrial Estate development in the northern Mojokerto region, consisting of two in Jetis District and two in Dawarblandong District. The research results can be an input for the industrial cluster development in the northern Mojokerto region.

Co-occurrence of climate-change induced and anthropogenic pressures in Central American key biodiversity areas

Central America hosts many key biodiversity areas (KBAs), areas which represent unique and irreplaceable ecosystems of global importance for species conservation. However, large extents of these areas are not under legal protection and could be threatened by pressures from land use change (e.g. deforestation and agricultural expansion), high human population density (e.g. population growth and urban sprawl) and climate-driven biome shifts. Here, we simulated future biome stability under the influence of climate change across KBAs in the Mesoamerican biodiversity hot spot and combined the results with projections of land use and population density up to the end of the 21st century. We applied four forcing scenarios based on two global climate models (GFDL-ESM4 and IPSL-CM6A-LR) and two shared socio-economic pathways (SSP1-2.6 and SSP3-7.0), which represent a range from low to high emission pathways. Our model projected decreased biome stability in 39%–46% of protected areas in KBAs, whereas this number even increased to 59%–60% for unprotected areas in KBAs (depending on the climate scenario). While human interferences in protected parts of KBAs are expected to be limited, large parts of unprotected areas in KBAs were projected to be pressured by multiple factors at once and are reason for concern. In particular, high human population pressures (>10 people km−2) emerged as a main threat over 30%–44% of the unprotected area in KBAs. These were largely accompanied by pressures from land use and sporadically reinforced by pressures from climate-driven biome shifts. Among the hot spots facing multiple high pressures are some of the last tropical dry and montane forest ecosystems in Central America, which stresses the need for urgent conservation action.

Integrated Spatial Simulation of Population and Urban Land Use: a Pan-European Model Validation

Spatial models jointly simulating population and land-use change provide support for policy-making, by allowing to explore territorial developments under alternative scenarios and resulting impacts in the environment, economy and society. However, their ability to reproduce observed spatial patterns is rarely evaluated through model validation. This lack of insight prevents researchers and policy-makers of fully grasping the ability of existing models to provide sensible projections of future land use and population density. In this article, we address this gap by performing a model validation of the LUISA Territorial Modelling Platform, a spatial model jointly simulating population and land use at a fine resolution (100 m) in the European Union and United Kingdom. In particular, we compare observed and simulated patterns of population and urban residential land-use change for the period of 1990–2015, and evaluate the model performance according to different degrees of urbanisation. The results show that model performance can vary depending on the context, even when the same data and methods are uniformly applied. The model performed consistently well in urban areas characterized by compact urban growth, but poorly where residential development occurred predominantly in scattered patterns across rural areas. Overall, the model tends to favour the formation of densely populated, highly accessible urban conglomerations, which often do not entirely correspond to the observed patterns. Based on the validation results, we propose directions for further model improvement and development. Model validation should be regarded as a critical step, and an integral part, in the process of developing models for policy support.

Predicting the evolution of the Lassa virus endemic area and population at risk over the next decades

Lassa fever is a severe viral hemorrhagic fever caused by a zoonotic virus that repeatedly spills over to humans from its rodent reservoirs. It is currently not known how climate and land use changes could affect the endemic area of this virus, currently limited to parts of West Africa. By exploring the environmental data associated with virus occurrence using ecological niche modelling, we show how temperature, precipitation and the presence of pastures determine ecological suitability for virus circulation. Based on projections of climate, land use, and population changes, we find that regions in Central and East Africa will likely become suitable for Lassa virus over the next decades and estimate that the total population living in ecological conditions that are suitable for Lassa virus circulation may drastically increase by 2070. By analysing geotagged viral genomes using spatially-explicit phylogeography and simulating virus dispersal, we find that in the event of Lassa virus being introduced into a new suitable region, its spread might remain spatially limited over the first decades.

Modelling Climate Change Impacts on Location Suitability and Spatial Footprint of Apple and Kiwifruit

The threats and opportunities faced by primary production industries from future climate changes can be adequately prepared for only with the guidance of model projections that can assist the development of robust policy and climate adaptation plans by governments and industries. We used continuous suitability models capable of reflecting incremental changes to project the suitability of locations across New Zealand for cultivating apple and kiwifruit in the mid- and late-century. These projections used future weather data from climate model simulations for two contrasting greenhouse gas (GHG) pathways: stringent GHG mitigation and unabated GHG emissions. To improve the suitability of the modelled temperature data, specifically for use with biologically driven, crop suitability models, we developed new bias-variance adjustments that preserved climate change signals within the data. Preliminary projections of land use across a range of alternative primary industries were obtained from a multinomial logit model incorporating continuous suitability scores as predictors. We refined the preliminary land-use projections by providing them as inputs into a simulation model of land use incorporating other drivers and constraints. This methodology provides a means for projecting future land use and the spatial footprints of primary industries, based on biological and econometric considerations, under different modelled climate change scenarios.

Impacts and Projections of Land Use and Demographic Changes on Ecosystem Services: A Case Study in the Guanzhong Region, China

Land use change and demographic factors directly or indirectly affect ecosystem services value, and the analysis of ecosystem services contributes to optimization of land planning, which is essential for regional sustainable development. In this study, ArcGIS 10.2, IDRISI 17.0 Selva and MATLAB software, value coefficient method, CA-Markov prediction model and population growth model were applied to analyze the spatial and temporal changes of land use trends and ecosystem service values in Guanzhong region, and further predict the impacts of land type changes and population changes on ecosystem services in the context of urbanization. Results showed that the expansion of construction land was the most intense, and the transfer process mainly crowded out arable land; the total ecosystem services value grew spatially in a “low center-high periphery” ring with large differences at the bottom, and forest land was the most important value provider. The total ecosystem services value was estimated to decline in the future, with low-value areas spreading northward and differences in the per capita ecosystem services value increasing. This study provides a reference for optimal simulation of urban expansion and ecological conservation.

Values and perceptions of landowners within remaining breeding territories of Eurasian Curlew Numenius arquata in Ireland

Habitat loss and degradation have been identified as some of the main threats to breeding Curlew (Numenius arquata) across much of Europe. In Ireland, marginal habitats such as rough or wet grasslands and peatlands have been fragmented or degraded by activities including afforestation, drainage and intensification. The management implemented by landowners directly affects Curlew breeding territories. However, the values and perceptions held by landowners whose lands contain Curlew breeding territories, or the factors driving the decisions behind farming practices in these areas are rarely considered when looking at the causes of changes in these bird populations. This study, as part of the Curlew Conservation Programme established in 2017, gathered data through the distribution of questionnaires to landowners found within three kilometres of Curlew breeding territories in Ireland. In this study, we identify the current land uses being employed in Curlew breeding territories, and query future projections of land use in these areas. We investigate landowners’ perceptions of the requirements to sustain favourable environments for breeding Curlew. We also explore landowner values with respect to farming. The landowners in this study identified habitat loss and predation as the main drivers for Curlew declines. The majority of farming systems in this study were cattle rearing, the sustainability of which is under threat across Ireland. The results indicate that these landowners are not financially motivated, however, the availability of financial aid and expert advice are listed by landowners as requirements for traditional farming practices to continue. These results give an insight to the lifestyle, values and perceptions owners of land adjacent or within Curlew breeding territories. This information can be used to design Curlew conservation programmes that align with these values.

Wilderness areas in a changing landscape: changes in land use, land cover, and climate.

Wilderness areas are not immune to changes in land use, land cover, and/or climate. Future changes will intensify the balancing act of maintaining ecological conditions and untrammeled character within wilderness areas. We assessed the quantitative and spatial changes in land use, land cover, and climate predicted to occur in and around wilderness areas by (1) quantifying projected changes in land use and land cover around wilderness areas; (2) evaluating if public lands surrounding wilderness areas can buffer future land‐use change; (3) quantifying future climate conditions in and around wilderness areas; and (4) identifying wilderness areas expected to experience the most change in land use, land cover, and climate. We used projections of land use (four variables), land cover (five variables), and climate (nine variables) to assess changes for 707 wilderness areas in the contiguous United States by mid‐21st century under two scenarios (medium‐low and high). We ranked all wilderness areas relative to each other by summing and ranking decile values for each land use, land cover, and climate variable and calculating a multivariate metric of future change. All wilderness areas were projected to experience some level of change by mid‐century. The greatest land‐use changes were associated with increases in agriculture, clear cutting, and developed land, while the greatest land cover changes were observed for grassland, forest, and shrubland. In 51.6% and 73.8% of wilderness areas, core area of natural vegetation surrounding wilderness was projected to decrease for the medium‐low and high scenarios, respectfully. Presence of public land did not mitigate the influence of land‐use change around wilderness areas. Geographically, projected changes occurred throughout the contiguous U.S., with areas in the northeast and upper Midwest projected to have the greatest land‐use and climate change and the southwestern U.S. projected to undergo the greatest land cover and climate change. Our results provide insights into potential future threats to wilderness areas and the challenges associated with wilderness stewardship and climate adaptation. Despite the high degree of protection and remoteness of wilderness areas, effective management and preservation of these lands must consider future changes in land use, land cover, and climate.

Quantifying the Impacts of Storm Surge, Sea Level Rise, and Potential Reduction and Changes in Wetlands in Coastal Areas of the Chesapeake Bay Region

Along the North Atlantic coasts of the United States, sea levels are rising at higher rates than the global average. Additionally, sea level rise (SLR) can cause reduction and redistribution of wetlands across the low-lying coastal landscape. This study applied a coupled storm surge and waves model to the Chesapeake Bay regions that are prone to SLR. Two historical storms of low and high wind intensity were simulated for current and potential future sea-level and land cover conditions. The future scenarios incorporated projections of local SLR and land use due to potential reduction and changes in coastal wetlands. Simulated flood depths were used in depth–damage functions to estimate prospective property damages, and were combined with population density information to estimate potential number of people at risk. The results showed that, depending on storm intensity, the total flooded area can increase from the baseline by 1.3–2.3 times in the minimum SLR scenario, and by 2.1–4.7 times in the maximum SLR scenario. The maximum SLR was estimated to cause approximately $5.8 billion to $8.6 billion in additional damages and potentially to affect 1–1.2 million people more than the number affected in current conditions. Results also suggest that the low-intensity storm was projected to have greater impacts in the future than the high-intensity storm today, indicating that even relatively weak storms may cause considerable damage to coastal communities in a future with SLR. Finally, flooding, property damage, and the number of people affected in the future scenarios were exacerbated by wetlands reduction and change—in other words, the protective services currently provided by natural lands in coastal areas can be diminished in the future with SLR.

Uncertainty of modelled bioenergy with carbon capture and storage due to variability of input data

AbstractUncertainty is inherent in modelled projections of bioenergy with carbon capture and storage (BECCS), yet sometimes treated peripherally. One source of uncertainty comes from different climate and soil inputs. We investigated variations in 70‐year UK projections of Miscanthus × giganteus (M × g), BECCS and environmental impacts with input data. We used cohort datasets of UKCP18 RCP8.5 climate projections and Harmonized World Soil Database (HWSD) soil sequences, as inputs to the MiscanFor bioenergy model. Low annual yield occurred 1 in 10 years as a UK‐average but yield uncertainty varied regionally, especially south and east England. BECCS projections were similar among cohorts, with variation resulting from climate cohorts of the same database ensemble (3.99 ± 0.14 t C ha−1 year−1) larger than uncertainty resulting from soil sequences in each grid block (3.96 ± 0.03 t C ha−1 year−1). This is supported by annual time series, displaying variable annual climate and a close yield–BECCS–climate relationship but partial correspondence of yield and BECCS with maximal soil variability. Each HWSD soil grid square contains up to 10 ranked soil types. Predominant soil commonly has over 50% coverage, indicating why BECCS from combined soil sequences were not significantly different from BECCS using the dominant soil type. Mean BECCS from the full climate ensemble combined with the full soil sequences, over the current area of cropping limits in England and Wales, is 3.98 ± 0.14 t C ha−1 year−1. The bioenergy crop has a mean seasonal soil water deficit of 65.79 ± 4.27 mm and associated soil carbon gain of 0.22 ± 0.03 t C ha−1 year−1, with bioenergy feedstock calculated at 131 GJ t−1 y−1. The uncertainty is specific to the input datasets and model used. The message of this study is to ensure that uncertainty is accounted for when interpreting modelled projections of land use impacts.

Are scenario projections overly optimistic about future yield progress?

Historical increases in agricultural production were achieved predominantly by large increases in agricultural productivity. Intensification of crop and livestock production also plays a key role in future projections of agricultural land use. Here, we assess and discuss projections of crop yields by global agricultural land-use and integrated assessment models. To evaluate these crop yield projections, we compare them to empirical data on attainable yields by employing a linear and plateauing continuation of observed attainable yield trends. While keeping in mind the uncertainties of attainable yields projections and not considering future climate change impacts, we find that, on average for all cereals on the global level, global projected yields by 2050 remain below the attainable yields. This is also true for future pathways with high technological progress and mitigation efforts, indicating that projected yield increases are not overly optimistic, even under systemic transformations. On a regional scale, we find that for developing regions, specifically for sub-Saharan Africa, projected yields stay well below attainable yields, indicating that the large yield gaps which could be closed through improved crop management, may also persist in the future. In OECD countries, in contrast, current yields are already close to attainable yields, and the projections approach or, for some models, even exceed attainable yields by 2050. This observation parallels research suggesting that future progress in attainable yields in developed regions will mainly have to be achieved through new crop varieties or genetic improvements. The models included in this study vary widely in their implementation of yield progress, which are often split into endogenous (crop management) improvements and exogenous (technological) trends. More detail and transparency are needed in these important elements of global yields and land use projections, and this paper discusses possibilities of better aligning agronomic understanding of yield gaps and yield potentials with modelling approaches.

Comparing the impact of future cropland expansion on global biodiversity and carbon storage across models and scenarios.

Land-use change is a direct driver of biodiversity and carbon storage loss. Projections of future land use often include notable expansion of cropland areas in response to changes in climate and food demand, although there are large uncertainties in results between models and scenarios. This study examines these uncertainties by comparing three different socio-economic scenarios (SSP1–3) across three models (IMAGE, GLOBIOM and PLUMv2). It assesses the impacts on biodiversity metrics and direct carbon loss from biomass and soil as a direct consequence of cropland expansion. Results show substantial variation between models and scenarios, with little overlap across all nine projections. Although SSP1 projects the least impact, there are still significant impacts projected. IMAGE and GLOBIOM project the greatest impact across carbon storage and biodiversity metrics due to both extent and location of cropland expansion. Furthermore, for all the biodiversity and carbon metrics used, there is a greater proportion of variance explained by the model used. This demonstrates the importance of improving the accuracy of land-based models. Incorporating effects of land-use change in biodiversity impact assessments would also help better prioritize future protection of biodiverse and carbon-rich areas.This article is part of the theme issue ‘Climate change and ecosystems: threats, opportunities and solutions’.

Global consequences of afforestation and bioenergy cultivation on ecosystem service indicators

Abstract. Land management for carbon storage is discussed as being indispensable for climate change mitigation because of its large potential to remove carbon dioxide from the atmosphere, and to avoid further emissions from deforestation. However, the acceptance and feasibility of land-based mitigation projects depends on potential side effects on other important ecosystem functions and their services. Here, we use projections of future land use and land cover for different land-based mitigation options from two land-use models (IMAGE and MAgPIE) and evaluate their effects with a global dynamic vegetation model (LPJ-GUESS). In the land-use models, carbon removal was achieved either via growth of bioenergy crops combined with carbon capture and storage, via avoided deforestation and afforestation, or via a combination of both. We compare these scenarios to a reference scenario without land-based mitigation and analyse the LPJ-GUESS simulations with the aim of assessing synergies and trade-offs across a range of ecosystem service indicators: carbon storage, surface albedo, evapotranspiration, water runoff, crop production, nitrogen loss, and emissions of biogenic volatile organic compounds. In our mitigation simulations cumulative carbon storage by year 2099 ranged between 55 and 89 GtC. Other ecosystem service indicators were influenced heterogeneously both positively and negatively, with large variability across regions and land-use scenarios. Avoided deforestation and afforestation led to an increase in evapotranspiration and enhanced emissions of biogenic volatile organic compounds, and to a decrease in albedo, runoff, and nitrogen loss. Crop production could also decrease in the afforestation scenarios as a result of reduced crop area, especially for MAgPIE land-use patterns, if assumed increases in crop yields cannot be realized. Bioenergy-based climate change mitigation was projected to affect less area globally than in the forest expansion scenarios, and resulted in less pronounced changes in most ecosystem service indicators than forest-based mitigation, but included a possible decrease in nitrogen loss, crop production, and biogenic volatile organic compounds emissions.

Biospheric feedback effects in a synchronously coupled model of human and Earth systems

Significant feedbacks in energy, agriculture, land use and the carbon cycle are identified for the twenty-first century when climate impacts on land are factored into climate projections so as to allow for two-way interactions between human and Earth systems. Fossil fuel combustion and land-use change are the two largest contributors to industrial-era increases in atmospheric CO2 concentration1. Projections of these are thus fundamental inputs for coupled Earth system models (ESMs) used to estimate the physical and biological consequences of future climate system forcing2,3. While historical data sets are available to inform past and current climate analyses4,5, assessments of future climate change have relied on projections of energy and land use from energy–economic models, constrained by assumptions about future policy, land-use patterns and socio-economic development trajectories6. Here we show that the climatic impacts on land ecosystems drive significant feedbacks in energy, agriculture, land use and carbon cycle projections for the twenty-first century. We find that exposure of human-appropriated land ecosystem productivity to biospheric change results in reductions of land area used for crops; increases in managed forest area and carbon stocks; decreases in global crop prices; and reduction in fossil fuel emissions for a low–mid-range forcing scenario7. The feedbacks between climate-induced biospheric change and human system forcings to the climate system—demonstrated here—are handled inconsistently, or excluded altogether, in the one-way asynchronous coupling of energy–economic models to ESMs used to date1,8,9.

Projections of Future Land Use in Bangladesh under the Background of Baseline, Ecological Protection and Economic Development

Land is one of the important input resources in a highly populous and land-scarce country such as Bangladesh. When different factors change (such as, geophysical, proximity, socioeconomic and climatic), there are dramatic changes in the spatial pattern of land uses. Thus, shedding light on the dynamics of land use and land cover changes has great importance for finding the changing pattern of land use in Bangladesh. In the present study, we predicted the land use and land cover changes from 2010 to 2030 under baseline, ecological protection priority and economic growth scenarios in Bangladesh. On this basis, we applied a previously developed Dynamics of Land Systems (DLS) model to simulate the changes in land uses according to the driving mechanisms. The findings indicate that cultivated land declines and built-up area expansion is common under all three scenarios. However, the future land use demand shows differences under different scenarios. The results under the ecological protection priority scenario shows that forest area and grassland will increase more, while under economic growth scenario, built-up area will expand dramatically in the future. The present research results furnish meaningful decision-making information for planners to conserve and/or exploit land resources in Bangladesh in a more sustainable manner.