Competition for land

A key challenge for humanity is how a future global population of 9 billion can all be fed healthily and sustainably. Here, we review how competition for land is influenced by other drivers and pressures, examine land-use change over the past 20 years and consider future changes over the next 40 years.Competition for land, in itself, is not a driver affecting food and farming in the future, but is an emergent property of other drivers and pressures. Modelling studies suggest that future policy decisions in the agriculture, forestry, energy and conservation sectors could have profound effects, with different demands for land to supply multiple ecosystem services usually intensifying competition for land in the future.In addition to policies addressing agriculture and food production, further policies addressing the primary drivers of competition for land (population growth, dietary preference, protected areas, forest policy) could have significant impacts in reducing competition for land. Technologies for increasing per-area productivity of agricultural land will also be necessary. Key uncertainties in our projections of competition for land in the future relate predominantly to uncertainties in the drivers and pressures within the scenarios, in the models and data used in the projections and in the policy interventions assumed to affect the drivers and pressures in the future.     

A review of global potentially available cropland estimates and their consequences for model‐based assessments

The world's population is growing and demand for food, feed, fiber, and fuel is increasing, placing greater demand on land and its resources for crop production. We review previously published estimates of global scale cropland availability, discuss the underlying assumptions that lead to differences between estimates, and illustrate the consequences of applying different estimates in model‐based assessments of land‐use change. The review estimates a range from 1552 to 5131 Mha, which includes 1550 Mha that is already cropland. Hence, the lowest estimates indicate that there is almost no room for cropland expansion, while the highest estimates indicate that cropland could potentially expand to over three times its current area. Differences can largely be attributed to institutional assumptions, i.e. which land covers/uses (e.g. forests or grasslands) are societally or governmentally allowed to convert to cropland, while there was little variation in biophysical assumptions. Estimates based on comparable assumptions showed a variation of up to 84%, which originated mainly from different underlying data sources. On the basis of this synthesis of the assumptions underlying these estimates, we constructed a high, a medium, and a low estimate of cropland availability that are representative of the range of estimates in the reviewed studies. We apply these estimates in a land‐change model to illustrate the consequences on cropland expansion and intensification as well as deforestation. While uncertainty in cropland availability is hardly addressed in global land‐use change assessments, the results indicate a large range of estimates with important consequences for model‐based assessments.     

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.     

Trade‐offs between land and water requirements for large‐scale bioenergy production

Bioenergy is expected to play an important role in the future energy mix as it can substitute fossil fuels and contribute to climate change mitigation. However, large‐scale bioenergy cultivation may put substantial pressure on land and water resources. While irrigated bioenergy production can reduce the pressure on land due to higher yields, associated irrigation water requirements may lead to degradation of freshwater ecosystems and to conflicts with other potential users. In this article, we investigate the trade‐offs between land and water requirements of large‐scale bioenergy production. To this end, we adopt an exogenous demand trajectory for bioenergy from dedicated energy crops, targeted at limiting greenhouse gas emissions in the energy sector to 1100 Gt carbon dioxide equivalent until 2095. We then use the spatially explicit global land‐ and water‐use allocation model MAgPIE to project the implications of this bioenergy target for global land and water resources. We find that producing 300 EJ yr^?1 of bioenergy in 2095 from dedicated bioenergy crops is likely to double agricultural water withdrawals if no explicit water protection policies are implemented. Since current human water withdrawals are dominated by agriculture and already lead to ecosystem degradation and biodiversity loss, such a doubling will pose a severe threat to freshwater ecosystems. If irrigated bioenergy production is prohibited to prevent negative impacts of bioenergy cultivation on water resources, bioenergy land requirements for meeting a 300 EJ yr^?1 bioenergy target increase substantially (+ 41%) – mainly at the expense of pasture areas and tropical forests. Thus, avoiding negative environmental impacts of large‐scale bioenergy production will require policies that balance associated water and land requirements.     

Gross changes in reconstructions of historic land cover/use for Europe between 1900 and 2010

Historic land‐cover/use change is important for studies on climate change, soil carbon, and biodiversity assessments. Available reconstructions focus on the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). This leads to a serious underestimation of land‐cover/use dynamics with impacts on the biogeochemical and environmental assessments based on these reconstructions. In this study, we quantified to what extent land‐cover/use reconstructions underestimate land‐cover/use changes in Europe for the 1900–2010 period by accounting for net changes only. We empirically analyzed available historic land‐change data, quantified their uncertainty, corrected for spatial‐temporal effects and identified underlying processes causing differences between gross and net changes. Gross changes varied for different land classes (largest for forest and grassland) and led to two to four times the amount of net changes. We applied the empirical results of gross change quantities in a spatially explicit reconstruction of historic land change to reconstruct gross changes for the EU27 plus Switzerland at 1 km spatial resolution between 1950 and 2010. In addition, the reconstruction was extended back to 1900 to explore the effects of accounting for gross changes on longer time scales. We created a land‐change reconstruction that only accounted for net changes for comparison. Our two model outputs were compared with five commonly used global reconstructions for the same period and area. In our reconstruction, gross changes led in total to a 56% area change (ca. 0.5% yr^?1) between 1900 and 2010 and cover twice the area of net changes. All global reconstructions used for comparison estimated fewer changes than our gross change reconstruction. Main land‐change processes were cropland/grassland dynamics and afforestation, and also deforestation and urbanization.     

Land management: data availability and process understanding for global change studies

In the light of daunting global sustainability challenges such as climate change, biodiversity loss and food security, improving our understanding of the complex dynamics of the Earth system is crucial. However, large knowledge gaps related to the effects of land management persist, in particular those human‐induced changes in terrestrial ecosystems that do not result in land‐cover conversions. Here, we review the current state of knowledge of ten common land management activities for their biogeochemical and biophysical impacts, the level of process understanding and data availability. Our review shows that ca. one‐tenth of the ice‐free land surface is under intense human management, half under medium and one‐fifth under extensive management. Based on our review, we cluster these ten management activities into three groups: (i) management activities for which data sets are available, and for which a good knowledge base exists (cropland harvest and irrigation); (ii) management activities for which sufficient knowledge on biogeochemical and biophysical effects exists but robust global data sets are lacking (forest harvest, tree species selection, grazing and mowing harvest, N fertilization); and (iii) land management practices with severe data gaps concomitant with an unsatisfactory level of process understanding (crop species selection, artificial wetland drainage, tillage and fire management and crop residue management, an element of crop harvest). Although we identify multiple impediments to progress, we conclude that the current status of process understanding and data availability is sufficient to advance with incorporating management in, for example, Earth system or dynamic vegetation models in order to provide a systematic assessment of their role in the Earth system. This review contributes to a strategic prioritization of research efforts across multiple disciplines, including land system research, ecological research and Earth system modelling.     

世界主要国家耕地动态变化及其影响因素

在世界人口持续攀升、全球耕地面积不断减少的背景下,探讨世界主要国家耕地变化其影响因素,对于分析预测未来世界耕地变化趋势、研究世界粮食安全具有积极意义。选择2050年人口过亿的17个国家和耕地面积排名前10的国家为研究对象,在分析1961—2007年耕地总量变化、人均耕地变化的基础上,探讨了耕地变化影响因素。研究结果表明,从20世纪60年代到2007年间的不同时期内,有越来越多的国家表现出耕地减少趋势,而人均耕地面积减少的国家个数高达90%以上。满足人口消费需求、城市化与经济发展是大多数国家耕地总量变化的主要动力;而人口快速增长、城市化则是导致许多国家人均耕地显著减少的重要原因。     

RCPs气候情景下挠力河流域耕地水土资源平衡效应模拟

气候变化背景下,如何耦合水土资源是当前土地资源利用亟待解决的关键问题之一.为揭示挠力河流域耕地水土资源平衡态势,本文以Landsat影像、数字高程模型(DEM)数据和气象台站数据为基本信息源,结合遥感和GIS技术,运用未来土地利用模拟模型定量模拟RCPs气候情景下耕地的水分盈亏状况.结果表明:挠力河流域耕地内部结构差异性变化导致水土资源呈现阶段性的平衡特征,1990年耕地水分盈亏状况良好,旱改水农业结构调整导致当地水田迅速扩张,2002年中度和重度缺水区大量增加,水分亏缺态势急剧恶化,至2014年耕地整体水分亏缺状况趋于缓和;通过对比不同空间分辨率及时间尺度下的模拟精度,确定最优模拟空间分辨率为200 m,最优模拟时间点为2038年;模拟结果显示,未来挠力河流域耕地整体呈现出明显的水分盈亏极化特征,即正常缺水、重度缺水和严重缺水区面积将进一步扩大,轻度缺水和中度缺水区呈现收缩态势,高水分盈亏程度指数区分布更加集中,局部高水分亏缺区面积进一步扩大.未来需针对该地区采取针对性的农田水分灌溉措施及耕地调整,以实现水土资源平衡利用.     

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.     

Impact of protein concentrate coproducts on net land requirement for European biofuel production

A methodology is proposed for calculating the net land area requirement for European biofuels, accounting for the substitution impact of animal feed protein coproducts such as dried distillers grains and solubles (DDGS) and rape meal. For example, when bioethanol is produced from cereal grain starch, grain protein is preserved in the DDGS coproduct. Each tonne of wheat DDGS has the potential to replace 0.59 tonnes of soy meal and 0.39 tonnes of cereals in EU animal feed, and the land area required for soy and cereal feed production offsets much of the land requirement for wheat bioethanol feedstock. While the land area needed for bioethanol from feed wheat in North West Europe is 0.40 ha t^?1, the net requirement after accounting for coproducts is just 0.03ha t^?1 of bioethanol produced, 6% of the gross land requirement. Calculated in this way, the net land area required to produce biofuel from EU cereal, rapeseed and sugar beet crops is much lower than the gross land requirement, and from cereal and sugar beet crops is less than the land requirement of biofuel from oil palm and sugar cane.     

Doubling protected land area may be inefficient at preserving the extent of undeveloped land and could cause substantial regional shifts in land use

Projection of land use and land-cover change is highly uncertain yet drives critical estimates of carbon emissions, climate change, and food and bioenergy production. We use new, spatially explicit land availability data in conjunction with a model sensitivity analysis to estimate the effects of additional land protection on land use and land cover. The land availability data include protected land and agricultural suitability and is incorporated into the Moirai land data system for initializing the Global Change Analysis Model. Overall, decreasing land availability is relatively inefficient at preserving undeveloped land while having considerable regional land-use impacts. Current amounts of protected area have little effect on land and crop production estimates, but including the spatial distribution of unsuitable (i.e., unavailable) land dramatically shifts bioenergy production from high northern latitudes to the rest of the world, compared with uniform availability. This highlights the importance of spatial heterogeneity in understanding and managing land change. Approximately doubling the current protected area to emulate a 30% protected area target may avoid land conversion by 2050 of less than half the newly protected extent while reducing bioenergy feedstock land by 10.4% and cropland and grazed pasture by over 3%. Regional bioenergy land may be reduced (increased) by up to 46% (36%), cropland reduced by up to 61%, pasture reduced by up to 100%, and harvested forest reduced by up to 35%. Only a few regions show notable gains in some undeveloped land types of up to 36%. Half of the regions can reach the target using only unsuitable land, which would minimize impacts on agriculture but may not meet conservation goals. Rather than focusing on an area target, a more robust approach may be to carefully select newly protected land to meet well-defined conservation goals while minimizing impacts to agriculture.     

权衡生态保护与经济发展的土地利用多情景模拟

从土地利用视角切入,首先对龙门山过渡带的生态服务功能重要性与生态脆弱性进行了综合评价,采用自然断点法将生态服务功能重要性与脆弱性计算值进行分级,以此为基础结合研究区现状已划定生态保护区,划分生态综合评价等级为Ⅴ级的区域为规划约束情景下土地利用限制转换区,划分生态综合评价等级为Ⅳ级、Ⅴ级的区域为生态保护情景下土地利用限制转换区。设置自然发展情景研究区土地利用规律保持2010-2015年不变,规划约束情景在自然发展情景基础上将耕地、林地与水域、草地向建设用地转化的概率分别降低30%、20%与10%,生态保护情景在自然发展情景基础上将耕地向建设用地转化概率降低30%并补充于耕地向林地转化之上,将林地、草地向建设用地转化的概率降低50%。基于多情景土地利用模拟结果,提取待权衡用地斑块,划定生态综合评价结果Ⅴ级、坡度25°、地方林线海拔3500m为判定阈值,结合现状地类、主体功能区划定等因素进行多重逻辑判定,将多情景模拟结果进行集成,权衡判定后的集成方案既能很好地保护生态环境,又能较好兼顾研究区经济发展。     

Land Reform and Land-Use Changes in the Lower Amazon: Implications for Agricultural Intensification

Land tenure has been considered one of the key factors that define patterns and change in land-use systems. This paper examines the implications of land reform for household decisions regarding patterns of land use, agricultural intensification, and forest conservation. We look at an Amazonian caboclo settlement in the Lower Amazon that had experienced land reform by the end of the 1980s. Results show that defined land tenure is not enough to guarantee agricultural intensification and forest conservation. In fact, several factors working at different scales are affecting land-use change in the region. At the settlement level, privatization of upland forest has led to an overall increase in cultivated land—pasture and annual crops—and increasing deforestation rates. However, at the farm-property level, different systems of agricultural production—intensive, extensive, or abandonment of land—occur according to availability of labor, and capital, and access to different natural resources.     

基于最小累积阻力模型的北京市生态用地规划研究

生态用地规划强调对区域生态系统结构与功能的保护,增强社会经济发展的生态环境支撑能力。从保障首都基本生态安全、改善大气环境质量、建设宜居城市的角度出发,通过对北京市生态重要性进行综合评价,明确北京市重要生态用地空间分布特征。在此基础上,采用最小累积阻力模型(MCR),以重要生态用地为"源",以土地覆被类型、距道路距离和距居民点距离作为阻力因子生成阻力面,模拟重要生态用地空间扩张过程,进而设置生态用地规划情景,并从景观连通性、生态功能保障度及与现状建设用地冲突情况等3个方面对不同情景下的生态用地规划方案进行保护效能评价,最终提出北京市生态用地的适宜规模和优化布局方案。研究结果表明:北京市重要生态用地总面积为9879 km~2,占市域总面积的60.20%;生态用地的适宜规模为12417 km~2,占市域总面积的75.67%,其中,平原区生态用地的适宜规模为2944 km~2,占平原区总面积的46.45%,主要分布于建成区的外围过渡地带;山区生态用地的适宜规模为9473 km~2,占山区总面积的94.05%。     

Challenges in using land use and land cover data for global change studies

Land use and land cover data play a central role in climate change assessments. These data originate from different sources and inventory techniques. Each source of land use/cover data has its own domain of applicability and quality standards. Often data are selected without explicitly considering the suitability of the data for the specific application, the bias originating from data inventory and aggregation, and the effects of the uncertainty in the data on the results of the assessment. Uncertainties due to data selection and handling can be in the same order of magnitude as uncertainties related to the representation of the processes under investigation. While acknowledging the differences in data sources and the causes of inconsistencies, several methods have been developed to optimally extract information from the data and document the uncertainties. These methods include data integration, improved validation techniques and harmonization of classification systems. Based on the data needs of global change studies and the data availability, recommendations are formulated aimed at optimal use of current data and focused efforts for additional data collection. These include: improved documentation using classification systems for land use/cover data; careful selection of data given the specific application and the use of appropriate scaling and aggregation methods. In addition, the data availability may be improved by the combination of different data sources to optimize information content while collection of additional data must focus on validation of available data sets and improved coverage of regions and land cover types with a high level of uncertainty. Specific attention in data collection should be given to the representation of land management (systems) and mosaic landscapes.     

耕地生态补偿实践与研究进展

摘要：耕地资源稀缺的特殊国情决定耕地需要承担着重要的职能,为此我国政府采取世界上最严格的耕地保护政策,但指挥和控制性的政策并没有发挥其应有的功效,因此,寻求一种保护稀缺耕地资源有效手段,是当今我国耕地资源保护与生态建设急需解决的问题。本文采用文献回顾法、归纳法对国内外相关的耕地生态补偿研究进行归纳分析。研究发现：国外对耕地的生态补偿的研究主要集中在美国和欧盟国家,研究案例主要涉及到有机农业、生态农业、生态多样性、湿地保护、自然资源保护、栖息地保护等方面。国外研究的热点主要是：1.生态补偿定量核算。试图量化耕地的外部效益,为补偿标准建立提供参考。2.生态保护成本。保护成本核算能确保对土地所有者或者保护者充分补偿。3.补偿的效率分析。它是评价补偿工具成败的一种有效手段。4.补偿的空间外部性。能确定涉及到的利益相关者。总之,国外的研究能够形成翔实地块数据并对已做决策效果进行分析和评价,而我国对具有生态功能价值和社会保障价值的耕地生态补偿的研究涉及较少,还处于探索阶段。国外的研究对于推动我国耕地生态补偿研究有很好的促进作用,借鉴国外发展模式与经验,根据我国国情与耕地生态补偿发展状况提出建立耕地生态补偿机制的政策建议。     

Land use and cover with intensity of agriculture for Canada from satellite and census data

Aim To develop the first national databases on land use and agricultural land use intensity in Canada for a wide variety of environmental monitoring applications. Location Canada. Methods In this paper, we describe a new system for the construction of both land use and land use intensity (within agricultural regions) called LUCIA (land use and cover with intensity of agriculture). Our methodology combines the highly detailed Canadian Census of Agriculture and recent growing season composites derived from the SPOT4/VEGETATION sensor. Census data are of much coarser resolution than the remotely sensed data but, by removing non‐agricultural pixels from each census sampling area, we were able to refine the census data sufficiently to allow their use as ground truth data in some areas. The ‘refined’ census data were then used in the final step of an unsupervised classification of the remotely sensed data. Results and main conclusions The results of the land use classification are generally consistent with the input census data, indicating that the LUCIA output reflects actual land use trends as determined by national census information. Land use intensity, defined as the principal component of census variables that relate to agricultural inputs and outputs (e.g. chemical inputs, fertilizer inputs and manure outputs), is highest in the periphery of the great plains region of central Canada but is also very high in southern Ontario and Québec.