scholarly journals Land-use harmonization datasets for annual global carbon budgets

2021 ◽  
Vol 13 (8) ◽  
pp. 4175-4189
Author(s):  
Louise Chini ◽  
George Hurtt ◽  
Ritvik Sahajpal ◽  
Steve Frolking ◽  
Kees Klein Goldewijk ◽  
...  

Abstract. Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for simulations of the 6th Coupled Model Intercomparison Project (CMIP6), has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual wood harvest data updates from the Food and Agriculture Organization (FAO) of the United Nations for dataset years after 2015 and the History Database of the Global Environment (HYDE) gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of 1 or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use-change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and dynamic global vegetation models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil as far back as 1950. From 1951 to 2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for the World Climate Research Programme's CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100 000 km2) and in the year 2009 for cropland (difference of 77 000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates, including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time lags due to the multiple input dataset and model latencies.

2021 ◽  
Author(s):  
Louise Chini ◽  
George Hurtt ◽  
Ritvik Sahajpal ◽  
Steve Frolking ◽  
Kees Klein Goldewijk ◽  
...  

Abstract. Land-use change has been the dominant source of anthropogenic carbon emissions for most of the historical period, and is currently one of the largest and most uncertain components of the global carbon cycle. Advancing the scientific understanding on this topic requires that the best data be used as input to state-of-the-art models in well-organized scientific assessments. The Land-Use Harmonization 2 dataset (LUH2), previously developed and used as input for CMIP6 simulations, has been updated annually to provide required input to land models in the annual Global Carbon Budget (GCB) assessments. Here we discuss the methodology for producing these annual LUH2-GCB updates and extensions which incorporate annual FAO wood harvest data updates for dataset years after 2015 and HYDE gridded cropland and grazing area data updates (based on annual FAO cropland and grazing area data updates) for dataset years after 2012, along with extrapolations to the current year due to a lag of one or more years in the FAO data releases. The resulting updated LUH2-GCB datasets have provided global, annual gridded land-use and land-use change data relating to agricultural expansion, deforestation, wood harvesting, shifting cultivation, regrowth and afforestation, crop rotations, and pasture management and are used by both bookkeeping models and Dynamic Global Vegetation Models (DGVMs) for the GCB. For GCB 2019, a more significant update to LUH2 was produced, LUH2-GCB2019 (https://doi.org/10.3334/ORNLDAAC/1851, Chini et al., 2020b), to take advantage of new data inputs that corrected cropland and grazing areas in the globally important region of Brazil, as far back as 1950. From 1951–2012 the LUH2-GCB2019 dataset begins to diverge from the version of LUH2 used for CMIP6, with peak differences in Brazil in the year 2000 for grazing land (difference of 100,000 km2) and in the year 2009 for cropland (difference of 77,000 km2), along with significant sub-national reorganization of agricultural land-use patterns within Brazil. The LUH2-GCB2019 dataset provides the base for future LUH2-GCB updates including the recent LUH2-GCB2020 dataset, and presents a starting point for operationalizing the creation of these datasets to reduce time-lags due to the multiple input dataset and model latencies.


2021 ◽  
Vol 14 (10) ◽  
pp. 6467-6494
Author(s):  
Abhijeet Mishra ◽  
Florian Humpenöder ◽  
Jan Philipp Dietrich ◽  
Benjamin Leon Bodirsky ◽  
Brent Sohngen ◽  
...  

Abstract. Out of 1150 Mha (million hectares) of forest designated primarily for production purposes in 2020, plantations accounted for 11 % (131 Mha) of this area and fulfilled more than 33 % of the global industrial roundwood demand. However, adding additional timber plantations to meet increasing timber demand intensifies competition for scarce land resources between different land uses such as food, feed, livestock and timber production. Despite the significance of plantations with respect to roundwood production, their importance in meeting the long-term timber demand and the implications of plantation expansion for overall land-use dynamics have not been studied in detail, in particular regarding the competition for land between agriculture and forestry in existing land-use models. This paper describes the extension of the modular, open-source land system Model of Agricultural Production and its Impact on the Environment (MAgPIE) using a detailed representation of forest land, timber production and timber demand dynamics. These extensions allow for a better understanding of the land-use dynamics (including competition for land) and the associated land-use change emissions of timber production. We show that the spatial cropland patterns differ when timber production is accounted for, indicating that timber plantations compete with cropland for the same scarce land resources. When plantations are established on cropland, it causes cropland expansion and deforestation elsewhere. Using the exogenous extrapolation of historical roundwood production from plantations, future timber demand and plantation rotation lengths, we model the future spatial expansion of forest plantations. As a result of increasing timber demand, we show a 177 % increase in plantation area by the end of the century (+171 Mha in 1995–2100). We also observe (in our model results) that the increasing demand for timber amplifies the scarcity of land, which is indicated by shifting agricultural land-use patterns and increasing yields from cropland compared with a case without forestry. Through the inclusion of new forest plantation and natural forest dynamics, our estimates of land-related CO2 emissions better match with observed data, in particular the gross land-use change emissions and carbon uptake (via regrowth), reflecting higher deforestation with the expansion of managed land and timber production as well as higher regrowth in natural forests and plantations.


2020 ◽  
Author(s):  
Katherine V. Calvin ◽  
Abigail Snyder ◽  
Xin Zhao ◽  
Marshall Wise

Abstract. The world has experienced a vast increase in agricultural production since the middle of the last century. Agricultural land area has also increased at the expense of natural lands over this period, though at a lower rate than production. Future changes in land use and cover have important implications not only for agriculture but for energy, water use, and climate. However, these future changes are driven by a complex combination of uncertain socioeconomic, technological, and other factors. Estimates of future land use and land cover differ significantly across economic models of agricultural production, and efforts to evaluate these economic models over history have been limited. In this study, we use an economic model of land use, gcamland, to systematically explore a large set of model parameter perturbations and alternate methods for forming expectations about uncertain crop yields and prices. We run gcamland simulations with these parameter sets over the historical period in the United States to explore model fitness and to identify combinations that improve fitness. We find that an adaptive expectation approach minimizes the error between simulated outputs and observations, with parameters that suggest that for most crops landowners put a significant weight on previous information. Interestingly, for corn, where ethanol policies have led to a rapid growth in demand, the resulting parameters show that a larger weight is placed on more recent information. We conclude with the observation that historical modeling exercises such as this study are valuable both for understanding real world drivers of land use change and for informing modeling of future land use change.


2019 ◽  
Vol 16 (2) ◽  
pp. 136
Author(s):  
Rangga Olenka ◽  
Adrimas Adrimas ◽  
Melinda Noer

ABSTRACTEarly detection is important to looking at the phenomenon of massive land use changes. Karimun Regency is one of the areas designated as one of the National Strategic Areas (KSN) for the benefit of economic growth. In addition, parts of the Karimun Regency are also designated as Free Trade Zone (FTZ). This has led to changes in land use patterns. This study analyzes changes in land use in Karimun Regency and its driving factors. Analysis of land use changes was carried out using land use map  and socio-economic data in 2008 - 2017. Methods of data analysis using spatial analysis and analysis of driving factors. The results showed that there were significant changes that occurred in land use. The rate of forest conversion and the decline in the area of agricultural land are very alarming. Growth of the built up area continues to increase. Development pattern of built area only concentrates on center of economic activity that already exists and also on transportation routes. Meanwhile the drivers of change in land use vary. Economic factors such as GRDP Karimun Regency and Investment and social factors such as urbanization and residents working in the primary sector drives land use change in Karimun Regency in 2008 – 2017. Key words: land use, land use change, driven factor ABSTRAKDeteksi dini penting dalam melihat fenomena perubahan penggunaan tanah yang masif. Kabupaten Karimun merupakan salah satu wilayah yang ditetapkan sebagai salah satu Kawasan Strategis Nasional (KSN) untuk kepentingan pertumbuhan ekonomi. Selain itu sebagian wilayah Kabupaten Karimun juga ditetapkan sebagai Kawasan Perdagangan Bebas dan Pelabuhan Bebas (Free Trade Zone). Hal tersebut mendorong perubahan pola penggunaan tanah. Studi ini menganalisis perubahan penggunaan tanah dan faktor pendorongnya yang terjadi di Kabupaten Karimun. Analisis perubahan penggunaan tanah dilakukan menggunakan peta penggunaan tanah dan data sosial ekonomi pada tahun 2008 - 2017. Metode analisis data menggunakan analisis spasial dan analisis faktor pendorong. Hasil penelitian menunjukkan bahwa ada perubahan signifikan yang terjadi pada penggunaan tanah. Laju konversi hutan sangat mengkhawatirkan. Pertumbuhan area terbangun terus meningkat. Pola pengembangan area terbangun hanya berkonsentrasi pada pusat kegiatan ekonomi yang sudah ada dan juga pada jalur transportasi. Sementara itu pendorong perubahan penggunaan tanah bervariasi. Faktor ekonomi seperti PDRB Kabupaten Karimun dan Investasi sedangkan faktor sosial seperti urbanisasi dan penduduk yang bekerja di sektor primer mendorong perubahan penggunaan tanah di Kabupaten Karimun tahun 2008 – 2017.  Kata Kunci: penggunaan tanah, perubahan penggunaan tanah, faktor pendorong.


Author(s):  
Yujuan Gao ◽  
Jianli Jia ◽  
Beidou Xi ◽  
Dongyu Cui ◽  
Wenbing Tan

The heavy metal pollution induced by agricultural land use change has attracted great attention. In this study, the divergent response of bioavailability of heavy metals in rhizosphere soil to different...


Land ◽  
2021 ◽  
Vol 10 (3) ◽  
pp. 286
Author(s):  
Dingrao Feng ◽  
Wenkai Bao ◽  
Meichen Fu ◽  
Min Zhang ◽  
Yiyu Sun

Land use change plays a key role in terrestrial systems and drives the process of ecological pattern change. It is important to investigate the process of land use change, predict land use patterns, and reveal the characteristics of land use dynamics. In this study, we adopted the Markov model and future land use (FLUS) model to predict the future land use conditions in Xi’an city. Furthermore, we investigated the characteristics of land use change from a novel perspective, i.e., via establishment of a complex network model. This model captured the characteristics of the land use system during different periods. The results indicated that urban expansion and cropland loss played an important role in land use pattern change. The future gravity center of urban development moved along the opposite direction to that from 2000 to 2015 in Xi’an city. Although the rate of urban expansion declined in the future, urban expansion remained the primary driver of land use change. The primary urban development directions were east-southeast (ENE), north-northeast (NNE) and west-southwest (WSW) from 1990 to 2000, 2000 to 2015, and 2015 to 2030, respectively. In fact, cropland played a vital role in land use dynamics regarding all land use types, and the stability of the land use system decreased in the future. Our study provides future land use patterns and a novel perspective to better understand land use change.


Author(s):  
Allison Neil

Soil properties are strongly influenced by the composition of the surrounding vegetation. We investigated soil properties of three ecosystems; a coniferous forest, a deciduous forest and an agricultural grassland, to determine the impact of land use change on soil properties. Disturbances such as deforestation followed by cultivation can severely alter soil properties, including losses of soil carbon. We collected nine 40 cm cores from three ecosystem types on the Roebuck Farm, north of Perth Village, Ontario, Canada. Dominant species in each ecosystem included hemlock and white pine in the coniferous forest; sugar maple, birch and beech in the deciduous forest; grasses, legumes and herbs in the grassland. Soil pH varied little between the three ecosystems and over depth. Soils under grassland vegetation had the highest bulk density, especially near the surface. The forest sites showed higher cation exchange capacity and soil moisture than the grassland; these differences largely resulted from higher organic matter levels in the surface forest soils. Vertical distribution of organic matter varied greatly amongst the three ecosystems. In the forest, more of the organic matter was located near the surface, while in the grassland organic matter concentrations varied little with depth. The results suggest that changes in land cover and land use alters litter inputs and nutrient cycling rates, modifying soil physical and chemical properties. Our results further suggest that conversion of forest into agricultural land in this area can lead to a decline in soil carbon storage.


Author(s):  
A. V. Prishchepov ◽  
F. Schierhorn ◽  
N. Dronin ◽  
E. V. Ponkina ◽  
D. Müller

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