Historical Land Use And Land Cover Change Research Articles

Spatiotemporal Characteristics of Land Cover Change in the Yellow River Basin over the Past Millennium

Investigating the ecological and environmental impacts stemming from historical land use and land cover change (LUCC) holds paramount importance in systematically comprehending the fundamental human-land relationship, a pivotal focus within geographical research. The Yellow River Basin (YRB), often referred to as the cradle of Chinese civilization, ranks as the fifth-largest river basin globally. Early inhabitants made significant alterations to the landscape, resulting in substantial damage to natural vegetation, giving rise to prominent regional ecological challenges. By now, the examination of historical LUCC in the YRB over the past millennium remains in the qualitative research stage, primarily due to the limited availability of high-confidence gridded historical LUCC data. This study aims to advance the current historical LUCC research in the YRB from primarily qualitative analysis to an exploration incorporating timing, positioning, and quantification. Based on reconstructed historical cropland, forest, and grassland grid data of 10 km × 10 km from 1000 AD to 2000 AD, the degree of cropland development and the depletion of forests and grasslands were calculated, respectively. Then, the kernel density method was employed for spatiotemporal analysis and interpretation of dynamic changes in land cover. Subsequently, a cartographic visualization depicting the migration trajectories of the land cover gravity centers was generated, allowing for an assessment of the distance and direction of the centroids’ movement of cropland, forest, and grassland. The results indicate that the cropland coverage in the YRB escalated from the initial 11.65% to 29.97%, while the forest and grassland coverage dropped from 63.36% to 44.49%. The distribution of cultivated land continually expanded outward from the southeast of the Loess Plateau and the southwest of the North China Plain. All three types of land cover experienced a westward shift in their gravity centers between 1000 and 2000 AD. Besides the population growth and technological advancements, the regime shifts induced by wars, along with land use policies in distinct periods, always served as the predominant factors influencing the conversion between different land covers. This research will present a paradigmatic regional case study contributing to the investigation of historical changes in land use and land cover. Additionally, it will offer historical perspectives beneficial for the advancement of China’s objectives in “Ecological Conservation and High-Quality Development of the Yellow River Basin”.

Land use-land cover change in the Tano basin, Ghana and the implications on sustainable development goals

The changes in land use and land cover (LULC) contribute to carbon emissions that lead to climate change and global warming. Obtaining information on LULC change is of necessity to ensure land transformation planning, and anthropogenic and natural impact evaluation. The objective of this study is to analyze the historical changes in LULC in the Tano River Basin of Ghana, to provide scientific information for decision-making on achieving sustainable development. A supervised classification of Landsat images (1986, 2010, and 2020) using the Random Forest algorithm was performed, as well as a post-classification comparison of LULC maps in terms of area and size. A “from–to” matrix was used to identify the changes in LULC that occurred between the periods 1986–2010, 2010–2020, and 1986–2020. The results show an overall classification accuracy of 88.9, 88.5, and 88% for LULC maps for the years 1986, 2010, and 2020, respectively. Between the period 1986 and 2020, there is a conversion of the greater part of dense forest to open forest, and subsequently to settlement and cropland as a major historical LULC change pattern in the Tano basin. Cropland and Settlement increased at the rate of 24.8 km/yr and 1.5 km/yr respectively, while Dense forest and Open forest decreased at the rate of 298.4 km/yr and 173.9 km/yr over the period 1986 to 2020. The study outputs are not only useful for formulating and implementing national policies and programs but also, can contribute to assessing and monitoring progress towards attaining Sustainable Development Goal 13 (climate action).

Cell-level coupling of a mechanistic model to cellular automata for improving land simulation

ABSTRACT The land use and land cover change (LUCC) process is crucial for climate and environmental change studies. Cellular automata (CA) models based on machine learning techniques have commonly been used to simulate LUCC. However, conventional CA models can only capture the historical relationship between driving forces and LUCC through statistics. Climate change significantly affects LUCC, especially natural vegetation. The statistical relationship between driving forces and LUCC may change with the climate. Furthermore, the existing coupled models of CA and mechanistic models are only loosely coupled in terms of the quantity of land demand provided by mechanistic models, which denotes that mechanistic models do not directly guide CA models in simulating spatial land dynamics. Thus, herein, a novel model that couples Lund Potsdam Jena (LPJ), a mechanistic model, and CA at the cell level is proposed to consider the mechanisms and statistics in LUCC simulations. The proposed coupled model (LPJ-FLUS) is validated by comparison with two historical LUCC simulations in China from 2001 to 2010 and 2015. The results show that the proposed coupled model affords higher simulation accuracy, especially on natural vegetation, compared to the two conventional CA models. The overall Figure of Merit value of the LPJ-FLUS model in the historical LUCC simulations is about 5% higher than that of the conventional CA model, reaching 23.37%, and is even 8% higher for some natural vegetation types. The proposed model is employed to predict the future LUCC under two SSP-RCP scenarios in China from 2015 to 2100. The simulation results show that the proposed model effectively combines the strengths of LPJ and CA, retaining the high spatial resolution of CA while representing the spatial possibilities of LUCC under different future climate scenarios assessed by LPJ. The quantitative validation results show that the simulation results of the LPJ-FLUS model are more spatially correlated with the LPJ model than those of conventional CA models. The proposed LPJ-FLUS model is a valuable attempt toward tightly coupling mechanistic and CA models at the cell level. Additionally, it has promising potential for high spatial resolution LUCC simulations and environmental impact analysis under future extreme climate scenarios.

Modeling on Urban Land Use Characteristics and Urban System of the Traditional Chinese Era (1930s) Based on the Historical Military Topographic Map

The quantitative urban system structure in historical periods and the long time-scale urban land area grid dataset with spatial attributes are important for land use and land cover change (LUCC) research. In this study, we aimed to measure the area of county level and above cities in mainland China in the 1930s, also known as the traditional Chinese era (TCE), using a geographic information system (GIS) model and 1:50,000 military topographic maps. Furthermore, we aimed to identify the structure and characteristics of the urban system in the TCE according to the administrative area division using methods such as the rank size law. The results of this study revealed that 1265 county level and above cities existed in the TCE, including 25 provincial level or above cities, 179 prefectural level cities, and 1061 county level cities. The total land area of all of the cities was 1396.48 km2, with a mean value of 1.1 km2 and a standard deviation of 2.37 km2. The rank-size analysis indicated that the urban system in TCE was characterized by large cities with insignificant development (q = 0.829 < 1, R2 = 0.905). The results of the Lorenz curve and Moran analyses showed that the spatial distribution of the urban systems in China during the traditional period exhibited nonuniform agglomeration. Large-scale military topographic maps of historical periods have proven to be a good source for land use reconstruction. The 1° × 1° grid urban land area dataset constructed based on a GIS model in the TCE is important for future research on historical LUCC and can provide basic data for climate change models, urban economic history, and other disciplines.

A new estimation of carbon emissions from land use and land cover change in China over the past 300 years

Scientific estimation of carbon emissions induced by historical land use and land cover change (LUCC) can improve the accuracy of terrestrial ecosystem carbon budget estimates and deepen understanding of the future carbon-sink potential of terrestrial ecosystems. The present study, using historical-document-based data for provincial cropland, forest, and grassland area in China, and experimental-data-based information for provincial vegetation and soil organic carbon density, re-estimates China's LUCC-induced carbon emissions for 1700–1980 using a bookkeeping model in which we updated tabulated functions for carbon losses and gains. The past 300 years have witnessed a dramatic LUCC in China. The cropland area has increased by 67.11 million ha, while the forest and grassland areas have decreased by 127.96 million ha and 16.72 million ha, respectively. Accordingly, the net carbon emissions for 1700–1980 are 6.17–12.35 Pg C, with 8.55 Pg C in the moderate scenario. Among the contributing factors, deforestation was the largest carbon source, accounting for over 90 % of the total carbon emissions. According to our estimates, over 70 % of carbon emissions were caused by harvesting wood, while <30 % were from converting forest and grassland to cropland. Spatially, for the whole period, carbon emissions in southwestern China (Chuan-Yu, Yunnan, and Guangxi), northeastern China (Liaoning, Jilin, and Heilongjiang), and parts of northwestern China (Gan-Ning, Qinghai, and Xinjiang) were as high as 6.03 Pg C, accounting for 70 % of the total carbon emissions. Extending previous studies, we updated the historical LUCC data, carbon density data, and tabulated functions for carbon losses and gains. The estimation results objectively reveal the historical spatiotemporal changes in LUCC-induced emissions.

Global effects of different types of land use and land cover changes on near-surface air temperature

Understanding the climate effect of land use and land cover change (LULCC) is critical for guiding human activities towards environmental sustainability. Previous studies have reported the climate effects of global deforestation, vegetation greening and crop cultivation changes. However, the contribution of each type of land state, land transition and land management to LULCC's climate effects remain underexamined. In this study, we estimated global biophysical temperature effects of LULCC using CMIP6 climate models, with special attention on the relative contribution (RC) of 12 land state changes, 113 land transitions and 10 land managements. The results show a large difference in the simulated LULCC's temperature effect between CESM2 and UKESM1–0-LL, and the two models even disagree in the sign of LULCC's effects in most of northern hemisphere except for autumn. Based on the weighted mean of two models, we found that historical LULCC has exerted a global warming effect at a rate of 0.0025 °C/century, with the largest warming effect in autumn. Spatially, a significant (p < 0.05) cooling effect is found from 60°N to 40°N, while the warming trend dominates the areas from 40°N to 30°S. Based on regression modelling, historical changes in forested/non-forested secondary land, urban land and cropland have contributed over 70% to LULCC's temperature effect, with land transitions from secondary land to cropland and from cropland to urban land dominating the climate effect at global scale. For land management, the climate effect of irrigation is larger than that of nitrogen fertilizer application. Furthermore, the application of nitrogen fertilizer for C3 plant has larger impacts compared to C4 plants, while similar effects of irrigation are observed for different types of croplands. Besides, the large difference in temperature effect between CESM2 and UKESM1–0-LL may be the difference in the forestland and cropland changes. Our study calls for explicit examination of the climate effect induced by different types of land state-change, land transition and land management for developing targeted land use policies in the future.

Rescaling the land rush? Global political ecologies of land use and cover change in key scenario archetypes for achieving the 1.5 °C Paris agreement target

ABSTRACT Advancing future-oriented perspectives in political ecology and critical agrarian studies, this paper examines projected land use and land cover change (LULCC) dynamics in four ‘archetypal’ scenarios foregrounded by the IPCC for limiting global warming to 1.5°C by 2100. Focusing on the Global South, we explore how these archetypes project a radical reversal of historical LULCC and rural population trends, potentially implying a considerable rescaling of contemporary land rush dynamics. Taken together, land-based climate mitigation futures highlight risks related to the (re)production of relative surplus populations through processes of rural enclosure and accumulation by dispossession in the Global South.

Historical Land Use and Land Cover Change of Eastern Nepal: A Case of Dharan Sub-Metropolitan City

Land use and land cover change (LUCC) has become an essential for monitoring and managing the natural resources, urban planning as well as sustainable development of any place. This study analyzes the historical LUCC during 1986-2020 of Dharan sub-metropolitan city (DSC) of Sunsari district, eastern Nepal. To analyze historical LUCC, LRMP (1986), ICIMOD (1990, 2000, 2010) and Google Earth Image (December, 2020) were used in the study. The results reveal the expansion of built-up areas by 500%, whereas agricultural land and forest cover decreased by 4% and6%, respectively, during the past 34 years. Mainly the growing built-up area encroached on the agricultural land, forest and river banks. The built-up area is expanded to the south-eastern, north-eastern and western direction from the core area. The built-up area is still likely to increase with high pace in the future, where need to give more attention to future possible urban hazards, urban pollutions and haphazard urbanization while making urban planning and policies.

Reconstruction of cropland change in North China Plain Area over the past 300 years

Abstract Land use and land cover change (LUCC) is not only a vital form of global change, but through biogeophysical and biogeochemical mechanisms, it also has a strong impact on the global and regional climate and environment change. The existing historical LUCC datasets still have many uncertainties that cause errors in climate and environment simulations. Reconstruction of historical LUCC on the regional scale is essential for improving the precision of global and national LUCC. In this study, we combined existing datasets with historical statistics and survey data to reconstruct cropland change in North China Plain Area over the past 300 years. Following systematic steps, a range of original methods from data sources and methods comparison, data re-calibration, time slices selection, data supplement, to cropland area fraction calculation were used. The cropland area at the county level was allocated into grid cells of 10 km × 10 km so as to achieve a high spatial resolution and precision. The results show that the cropland area change in North China Plain Area can be classified into two main stages: steady increase before 1954 and rapid decrease after 1954. The spatial distribution of cropland change over the past 300 years corresponded to the patterns of the total cropland change in North China Plain Area. From the late 17th century to the 1980s, the cropland area fraction in the plains increased and the cropland expanded to the hilly and coastal areas gradually. After that, the cropland area fraction in the plains decreased, especially in the southeastern of North China Plain Area. The total cropland area in North China Plain Area of our study is close to the results of most previous studies but the maps generated based on our dataset present local difference of cropland distribution more clearly than a recent important global dataset HYDE3.2. Our dataset of cropland area at 10 km × 10 km grid scale can also be used directly in climate and environment simulations to improve the data precision in North China Plain Area.

Attributing the Carbon Cycle Impacts of CMIP5 Historical and Future Land Use and Land Cover Change in the Community Earth System Model (CESM1)

AbstractHistorical global land use and land cover change (LULCC) emissions of 160 PgC represent a third of all human CO2 emissions from 1850 to 2010. Future land management decisions will have large impacts on the global carbon cycle, with scenarios ranging from continued deforestation and wood harvest to mitigation scenarios that reduce total emissions through afforestation and conversion to bioenergy. Here we present a systematic assessment of Community Earth System Model (CESM1) Coupled Model Intercomparison Project phase 5 (CMIP5) historic and projection simulations, with and without LULCC. For the historical period, CESM produced a Net LULCC flux of 123 PgC to the atmosphere, removing −130 PgC from ecosystems while increasing wood product pools by 7 PgC. Historical LULCC fluxes were equally divided between conversion and wood harvest fluxes. For the Representative Concentration Pathway (RCP) 4.5 afforestation scenario CESM produced a Net LULCC flux of 53 PgC to the atmosphere, removing −58 PgC out of the ecosystem and increasing wood product pools of 5 PgC. The afforestation offsets the Direct LULCC flux of 153 PgC with a negative Indirect LULCC flux of −94 PgC. For the RCP 8.5 high LULCC scenario, CESM produced a Net LULCC flux of 211 PgC, removing −227 PgC from ecosystems and increasing wood product pools of 15 PgC. The LULCC of the future RCP scenarios was dominated by wood harvest fluxes, which is a process that was not included in many of the CMIP5 models. The analysis framework also allowed the attribution of Indirect and Prior LULCC fluxes that offset the Direct LULCC fluxes in many cases.

Quantifying the Relative Importance of Direct and Indirect Biophysical Effects of Deforestation on Surface Temperature and Teleconnections

Abstract In this study, the authors linearize the surface energy budget equation that disentangles indirect effects (resulting from changes in downward shortwave and longwave radiation and air temperature) from direct biophysical effects (resulting from changes in surface albedo, evapotranspiration, and roughness length) of deforestation on land surface temperature. This formulation is applied to idealized deforestation simulations from two climate models and to realistic land-use and land-cover change (LULCC) simulations from 11 models, and the contribution of each underlying mechanism to surface temperature change is quantified. It is found that the boreal region experiences dominant indirect effects and the tropics experience dominant direct effects in all seasons in idealized deforestation simulations. The temperate region response differs in the two models. However, five out of seven models in response to realistic historical LULCC show a dominance of indirect effects in the temperate region. In response to future LULCC, three out of four models confirm the dominance of direct effects in the tropical region. It is found that indirect effects are always largely attributable to air temperature feedback and direct effects are essentially driven by changes in roughness length in both idealized and realistic simulations. Furthermore, teleconnections are shown to exist between deforested regions and the rest of the world, associated with the indirect effects. The study also shows that the partitioning between direct and indirect effects is highly model dependent, which may explain part of the intermodel spread found in previous studies comparing the total biophysical effects across models.

Cellular automata and Markov Chain (CA_Markov) model-based predictions of future land use and land cover scenarios (2015–2033) in Raya, northern Ethiopia

Little is known about the future land use and land cover (LULC) type in some parts of Ethiopia, but not in the study area. This study aims to predict and analyze the future scenarios of LULC (2015–2033) using cellular automata and Markov Chain model (CA_Markov) by taking into consideration the physical and socio-economic drivers of LULC dynamics. The historical LULC change data of 1984–1995, 1995–2015, and 1984–2015 were used as a baseline. Both transition rules and transition area matrix for the period 1984–1995, 1995–2015, and 1984–2015 were produced quantitatively using the Markov chain model. After that, the physical and socio-economic factors were standardized using fuzzy and then Multi-Criteria Evaluation (MCE) was used to produce the transition suitability image. The CA_Markov model was then applied as a standard contiguity filter of 5 × 5 to predict the 2033 LULC condition using the TerrSet Geospatial Modeling and Monitoring System software. The result indicated that forestland are predicted to increase by 108 sq km (44.5%), shrub/bush lands 710 sq km (20%), built-up area 286.2 sq km (48.3%), and grasslands 31 sq km (15%), respectively. However, significant reductions (losses) in a water body (Wb) 5.2 sq km (11.2%), croplands (Cl) 78.9 sq km (1.3%), barren lands (Bl) 800 sq km (27.4%), and floodplain area (Fp) 251.68 sq km (33.7%), respectively. Furthermore, the Pearson correlation result between the historical and predicted LULC type indicated that there are positive, strongly correlated, and are statistically significant relationships (r = 0.981, p = 0.000). The increase in forest land and reduction in barren and flood plain may benefit the study area. However, the decrease in the water body may contribute to the severity of drought in the area. This study may help to use as useful information to foster better decisions and improve policies in land use within the framework of sustainable land use planning system.

The role of protected areas in land use/land cover change and the carbon cycle in the conterminous United States.

Protected areas (PAs) cover about 22% of the conterminous United States. Understanding their role on historical land use and land cover change (LULCC) and on the carbon cycle is essential to provide guidance for environmental policies. In this study, we compiled historical LULCC and PAs data to explore these interactions within the terrestrial ecosystem model (TEM). We found that intensive LULCC occurred in the conterminous United States from 1700 to 2005. More than 3 million km2 of forest, grassland and shrublands were converted into agricultural lands, which caused 10,607Tg C release from land ecosystems to atmosphere. PAs had experienced little LULCC as they were generally established in the 20th century after most of the agricultural expansion had occurred. PAs initially acted as a carbon source due to land use legacies, but their accumulated carbon budget switched to a carbon sink in the 1960s, sequestering an estimated 1,642Tg C over 1700-2005, or 13.4% of carbon losses in non-PAs. We also find that PAs maintain larger carbon stocks and continue sequestering carbon in recent years (2001-2005), but at a lower rate due to increased heterotrophic respiration as well as lower productivity associated to aging ecosystems. It is essential to continue efforts to maintain resilient, biodiverse ecosystems and avoid large-scale disturbances that would release large amounts of carbon in PAs.

Downscaling land use and land cover from the Global Change Assessment Model for coupling with Earth system models

Abstract. The Global Change Assessment Model (GCAM) is a global integrated assessment model used to project future societal and environmental scenarios, based on economic modeling and on a detailed representation of food and energy production systems. The terrestrial module in GCAM represents agricultural activities and ecosystems dynamics at the subregional scale, and must be downscaled to be used for impact assessments in gridded models (e.g., climate models). In this study, we present the downscaling algorithm of the GCAM model, which generates gridded time series of global land use and land cover (LULC) from any GCAM scenario. The downscaling is based on a number of user-defined rules and drivers, including transition priorities (e.g., crop expansion preferentially into grasslands rather than forests) and spatial constraints (e.g., nutrient availability). The default parameterization is evaluated using historical LULC change data, and a sensitivity experiment provides insights on the most critical parameters and how their influence changes regionally and in time. Finally, a reference scenario and a climate mitigation scenario are downscaled to illustrate the gridded land use outcomes of different policies on agricultural expansion and forest management. Several features of the downscaling can be modified by providing new input data or changing the parameterization, without any edits to the code. Those features include spatial resolution as well as the number and type of land classes being downscaled, thereby providing flexibility to adapt GCAM LULC scenarios to the requirements of a wide range of models and applications. The downscaling system is version controlled and freely available.

Review of studies on land use and land cover change in Nepal

Land use and land cover (LULC) in Nepal has undergone constant change over the past few decades due to major changes caused by anthropogenic and natural factors and their impacts on the national and regional environment and climate. This comprehensive review of past and present studies of land use and land cover change (LUCC) in Nepal concentrates on cropland, grassland, forest, snow/glacier cover and urban areas. While most small area studies have gathered data from different sources and research over a short period, across large areas most historical studies have been based on aerial photographs such as the Land Resource Mapping Project in 1986. The recent trend in studies in Nepal is to focus on new concepts and techniques to analyze LULC status on the basis of satellite imagery, with the help of geographic information system and remote sensing tools. Studies based on historical documents, and historical and recent spatial data on LULC, have clearly shown an increase in cropland areas in Nepal, and present results indicating different rates and magnitudes. A decrease in forest and snow/glacier coverage is reported in most studies. Little information is available on grassland and urban areas from past research. The unprecedented rate of urbanization in Nepal has led to significant urban land changes over the past 30 years. Meanwhile, long term historical LUCC research in Nepal is required for extensive work on spatially explicit reconstructions on the basis of historical and primary data collection, including LULC archives and drivers for future change.

Reconstruction of cropland change over the past 300 years in the Jing-Jin-Ji area, China

Land-use and land-cover change (LUCC) has strongly influenced the global and regional climate and environmental change, especially over the last three centuries. Accurate reconstruction of historical LUCC is a key step for assessing the impact of LUCC on global environmental change. To fill in the gap of regional historical cropland reconstruction in North China and achieve a better understanding of the historical cropland change process, in this paper we reconstruct cropland change at the county level over the past 300 years in the Jing-Jin-Ji (Beijing–Tianjin–Hebei) area, China. The reconstruction is based on sources including gazetteers, statistics and survey documents, and the methods are composed of data calibration, data interpolation and correlation analysis of data. The results show that the cropland change in the Jing-Jin-Ji area fluctuated, which can be classified into five stages: rapid increase in 1677–1755 and 1916–1950, slight growth in 1755–1884, gentle decline in 1884–1916 and rapid decrease after 1950. Two peak values appeared in 1884 and 1950. The spatial distribution of cropland in the Jing-Jin-Ji area kept a steady expansion and the majority of cropland concentrated on the plain before 1911. After this, the spatial distribution of cropland became more even and there was a rapid increase in the eastern coastal region and the northern hilly region. After 1985, the Jing-Jin-Ji area has experienced rapid urbanization and cultivation ratios in most counties declined, especially in Beijing municipality. Our dataset of the cropland area at the county level can contribute to improving the precision of the global and national land-use and land-cover datasets.

Modeled historical land use and land cover for the conterminous United States

ABSTRACTThe landscape of the conterminous United States has changed dramatically over the last 200 years, with agricultural land use, urban expansion, forestry, and other anthropogenic activities altering land cover across vast swaths of the country. While land use and land cover (LULC) models have been developed to model potential future LULC change, few efforts have focused on recreating historical landscapes. Researchers at the US Geological Survey have used a wide range of historical data sources and a spatially explicit modeling framework to model spatially explicit historical LULC change in the conterminous United States from 1992 back to 1938. Annual LULC maps were produced at 250-m resolution, with 14 LULC classes. Assessment of model results showed good agreement with trends and spatial patterns in historical data sources such as the Census of Agriculture and historical housing density data, although comparison with historical data is complicated by definitional and methodological differences. The completion of this dataset allows researchers to assess historical LULC impacts on a range of ecological processes.

Understanding the effect of three decades of land use change on soil quality and biomass productivity in a Mediterranean landscape in Chile

Land-use and land-cover change (LUCC) can deeply alter soil quality (SQ), affecting important productivity functions like vegetation biomass. A further understanding of the history of LUCC is essential to explain natural or anthropic landscape cover. The Mediterranean region of central Chile has historically been affected by LUCC impacts on the vegetation gradient of the landscape, which ranges from natural cover to anthropic cover like grazing pastures and crop lands. The main objective of this study is to define the historical impact of LUCC on SQ in a Mediterranean landscape in central Chile. To conduct the study, historical LUCC trends between 1975 and 2011 were analyzed. A Soil Quality Index (SQI) was developed to comparatively assess six types of land use (Annual Crops, Perennial Crops, Grazing, Espinal, Dense Espinal and Native Forest); and finally, SQI was interpolated at landscape scale using the soil-adjusted vegetation index (SAVI) as an auxiliary variable. SAVI was selected to represent indirect information on vegetation biomass productivity. The results indicate that most LUCC dynamics were observed in the Espinal woodland, where agriculture and grazing activities have been developed historically. The SQI showed significant SQ deterioration when Native Forests (SQI=0.82) degrade and are transformed by anthropic interventions like Annual Crops (SQI=0.27), Perennial Crops (SQI=0.34) or Grassland (SQI=0.36). However, a slight improvement in SQ compared to the other land uses was identified in the Dense Espinal (SQI=0.46). Finally, the quality model at landscape scale showed clear differences in SQI values for all landscape covers.

Effects of land use and land cover on selected soil quality indicators in the headwater area of the Blue Nile basin of Ethiopia.

Understanding changes in soil quality resulting from land use and land management changes is important to design sustainable land management plans or interventions. This study evaluated the influence of land use and land cover (LULC) on key soil quality indicators (SQIs) within a small watershed (Jedeb) in the Blue Nile Basin of Ethiopia. Factor analysis based on principal component analysis (PCA) was used to determine different SQIs. Surface (0-15 cm) soil samples with four replications were collected from five main LULC types in the watershed (i.e., natural woody vegetation, plantation forest, grassland, cultivated land, and barren land) and at two elevation classes (upland and midland), and 13 soil properties were measured for each replicate. A factorial (2 × 5) multivariate analysis of variance (MANOVA) showed that LULC and altitude together significantly affected organic matter (OM) levels. However, LULC alone significantly affected bulk density and altitude alone significantly affected bulk density, soil acidity, and silt content. Afforestation of barren land with eucalypt trees can significantly increase the soil OM in the midland part but not in the upland part. Soils under grassland had a significantly higher bulk density than did soils under natural woody vegetation indicating that de-vegetation and conversion to grassland could lead to soil compaction. Thus, the historical LULC change in the Jedeb watershed has resulted in the loss of soil OM and increased soil compaction. The study shows that a land use and management system can be monitored if it degrades or maintains or improves the soil using key soil quality indicators.

A model based investigation of the relative importance of CO2-fertilization, climate warming, nitrogen deposition and land use change on the global terrestrial carbon uptake in the historical period

In this paper, using the fully coupled NCAR Community Earth System Model (CESM1.0.4), we investigate the relative importance of CO2-fertilization, climate warming, anthropogenic nitrogen deposition, and land use and land cover change (LULCC) for terrestrial carbon uptake during the historical period (1850–2005). In our simulations, between the beginning and end of this period, we find an increase in global net primary productivity (NPP) on land of about 4 PgCyr−1 (8.2 %) with a contribution of 2.3 PgCyr−1 from CO2-fertilization and 2.0 PgCyr−1 from nitrogen deposition. Climate warming also causes NPP to increase by 0.35 PgCyr−1 but LULCC causes a decline of 0.7 PgCyr−1. These results indicate that the recent increase in vegetation productivity is most likely driven by CO2 fertilization and nitrogen deposition. Further, we find that this configuration of CESM projects that the global terrestrial ecosystem has been a net source of carbon during 1850–2005 (release of 45.1 ± 2.4 PgC), largely driven by historical LULCC related CO2 fluxes to the atmosphere. During the recent three decades (early 1970s to early 2000s), however, our model simulations project that the terrestrial ecosystem acts as a sink, taking up about 10 PgC mainly due to CO2 fertilization and nitrogen deposition. Our results are in good qualitative agreement with recent studies that indicate an increase in vegetation production and water use efficiency in the satellite era and that the terrestrial ecosystem has been a net sink for carbon in recent decades.